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As Google’s Growth Falters, Microsoft Could Regain Momentum
By 24/7 Wall St. Wednesday, Apr. 01, 2009People sit under a Google logoitted.
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Facebook Yahoo! BuzzTwitter Linkedin Permalink Reprints Related Most of the recent news about Google (GOOG) has been bad. Online advertising posted a slow fourth quarter. That unexpectedly included both display ads and search marketing which has made Google one of the fastest growing large companies in America. Several Wall St. analysts have commented that Google’s search revenue’s rate of increase flattened out in January and February. Since the consensus among experts who cover the company is that revenue will rise 11% in the first quarter, a flat quarter would be devastating.

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One of the things that Wall St. hates about Google is that it does one thing better than any other company in the world, but that is all it does. Google Chrome browser, Google Earth, Google Maps, and YouTube have really made much money. Some of the features have not produced any revenue at all. If its search operation falters, Google’s run as the hottest tech company in the world could be over. (See pictures of Google Earth.)

At this point, Google is a $22 billion company. If the search business drops to a growth rate of 10% a year, it will take three years for Google’s sales to get to $30 billion. From the time Microsoft (MSFT) hit $22 billion in sales in 2000, it took the company less than three years to get to the $30 billion plateau. Then from 2002 to 2008, Microsoft’s sales doubled. The software business not only grew. Until recently, it grew quickly. (See pictures of Bill Gates.)

The assumption about Google’s prospects is that the search company is the next Microsoft. Twenty years ago, Microsoft had the hot hand. Sales of Windows and the company’s business and server software were stunning. The margins on some of Microsoft’s software franchises were over 70%. Then the hyper-growth stopped as the company’s market penetration of PCs and servers reached a saturation point. Microsoft’s stock never saw the level it hit in 2000 again. Without lucrative stock options, employees who wanted to make it rich moved to start-ups. The people who had been at the company thirty years were already rich. Many of them retired.

About seven years after Microsoft’s stock hit an all-time high, Google traded at $747, its peak. It now changes hands at $348, and if the company’s sales can only grow at 10% or 15%, the stock is not going back above $700, ever. The myth about companies like Microsoft and Google is that what they do is so important to business and consumers and so pervasive that the growth curve never flattens out. It does flatten at every company. No exceptions.

The press coverage of Google this week included a few pathetic announcements. Disney (DIS) will put some of its premium content on Google’s YouTube. That should be good for $10 million in revenue a year. Google is starting a $100 million venture capital arm which will make it the 1,000th largest venture operation in the world. In other words, it will not be managing enough venture money to matter. Then word came out that Hewlett-Packard (HPQ) might use Google’s operating system in some of its netbooks instead of Microsoft Windows. The important word in that report is “might.” The news that Google is adding thousands of employees a quarter and that the founders have bought a 747 or an aircraft carrier probably hit a high point two years ago.

Saying that Google is doing poorly is not the same as saying that Microsoft is doing well. What matters to Microsoft is that Google becomes less of a threat each day as it fails in its diversification attempts. Google’s cash flow does not continue to give it an almost limitless capital arsenal. Google has to consider cutting people in areas which will never be profitable. The entire ethos at Google is in the process of changing. Microsoft may be in third place in the search business, but it is in first place in software, which is still the larger industry.

Investors still ask Microsoft why it is in the video game business. There is not any reasonable answer. It is an awful business with poor margins. It has nothing to do with selling Windows. There may have been some idea that being in the hardware business would help the software business, but, if so, that idea didn’t work out a long time ago.

With the perceived playing field that Microsoft and Google operate on a bit more level now, they can race after the one market that could be substantial for either one or both of them, which is providing software and search on mobile devices. The smartphone, which is really a PC for the pocket, is part of the one-billion-units-per-year-in-sales handset industry. Providing the operating software and other key components for wireless devices is almost certainly the next big thing for tech companies from Google to Yahoo (YHOO) to Microsoft to Adobe (ADBE). Trying to milk more money out of the PC gets harder and harder. For the largest companies in the industry, it has become a zero sum game. (See pictures of the 50 best websites of 2008.)

For Google and Microsoft, the best days are over, unless one can dominate the handset world the way it did the universe of computers.

— Douglas A. McIntyre

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How to Use the New Google Web Search RSS Feeds

Written by Marshall Kirkpatrick / October 30, 2008 11:31 AM / 7 Comments

Google’s been the lone hold out among major search engines on RSS but the company quietly enabled feeds for web search results this week. The offering is pretty limited and frustrating, you have to go through Google Alerts to get an obscure RSS URL, but we offer a tutorial and some strategic advice in this post.

Web search RSS is useful for being alerted whenever search results for your keywords or link have changed; subscribing to at least a few searches will let you know when Google users are seeing something new in the first few pages of search results for your company name, for example.

How to Get the Feeds

All the other major search engines make it really easy to grab a feed for any web search, but Google is probably concerned about spammers finding bizarre and unscrupulous uses for its feeds. We’re all inconvenienced as a result.

To get a feed for a Google search you have to go to the web page for Google Alerts and set up an alert for your search. You can enter most queries here, including site: queries. (site:http://readwriteweb.com semantic for example.) You should select “web” instead of the default “comprehensive” if you’re just interested in tracking web search results.


“Feed” isn’t an option in the initial drop down menu of delivery options, you’ve got to select email first. After you’ve done that, look at your collection of alerts and click to edit the one you want by RSS. At this point “feed” is an option in the drop down menu. Select it and you’ll be shown an RSS URL. Throw that puppy in your favorite feed reader and you’re ready to rock and roll.

The feed will deliver any new links that show up in the top 20 search results for your query. That’s pretty limited, but most people don’t look beyond the first 20 results anyway. That means that this is good for high-level reputation tracking but not very good for discovery of new, more obscure pages of interest.

The RSS URLs that Google gives you are based on an arbitrary number and don’t contain the text characters of your query. That means you can’t build more feeds by simply editing the URLs, you have to go back in through Alerts and repeat the proccess for every feed of interest.

Update: One day after we wrote this post, the official Google Blog just announced the availability of feed alerts as well.

More Advanced Options

Here’s how we’re using the new Google search feeds. We’ve grabbed feed URLs for searches for A. our names, B. our company name, C. our company URL and (just for fun) one for each of those three items without the other two. For example: “Richard MacManus” -readwriteweb -http://readwriteweb.com.

That gave us a small pile of feeds, which we then ran through our favorite RSS splicing and deduplication service (we used Yahoo Pipes but if you’re not comfortable with Pipes then Feed.informer.com is really easy to use). We spliced all these feeds together, filtered for duplicates and then threw the resulting feed into our highest priority feed reading system.

Pipes_ editing _RWW Google Websearch Tracking_.jpg

Now we can track our high level reputations constantly, without being paranoid about it. We might do this for concept searches as well so that if someone new starts ranking really high for topics we specialize in (semantic web, RSS) then we’ll know about them and never look ignorant at parties.

If we were interested in getting an RSS feed for Google web search for discovery, more than just reputation tracking, we might do an “advanced search,” increase the results displayed from 10 to 100 and then use Dapper.net to scrape a feed of results from that page.

All of this is more complicated than it ought to be, but once you set up even the most basic feed options then you don’t have to think about it again. Though it isn’t perfect, we do appreciate Google making these feeds available.

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Search War: Yahoo! Opens Its Search Engine to Attack Google With An Army of Verticals

Written by Marshall Kirkpatrick / July 9, 2008 9:00 PM / 15 Comments

BossYahoo! is taking a bold step tonight: opening up its index and search engine to any outside developers who want to incorporate Yahoo! Search’s content and functionality into search engines on their own sites. The company that sees just over 20% of the searches performed each day believes that the new program, called BOSS (Build Your Own Search Service), could create a cadre of small search engines that in aggregate will outstrip their own market share and leave Google with less than 50% of the search market.

It’s an ambitious and exciting idea. It could also become very profitable when Yahoo! later enables the inclusion of Yahoo! search ads on sites using the BOSS APIs. BOSS will include access to Yahoo! web, news and image searches.

Partner Relationships

Websites wishing to leverage the BOSS APIs will be allowed to can blend in their own ranking input and change the presentation of results. There are no requirements for attribution to Yahoo! and there’s no limit on the number of queries that can be performed.

At launch Yahoo! BOSS will see live integrations with at least three other companies. Hakia will integrate their semantic parsing with the Yahoo! index and search, social browser plug-in Me.dium will use the data it’s collected to offer a social search tied to the Yahoo! index, and real-time sentiment search engine Summize was included in the BOSS demo – augmenting Yahoo News search results with related Twitter messages.

More extensive customization and integration with large media companies will be performed with assistance from Yahoo! and ad-free access to the APIs will be made available to the Computer Science departments of academic institutions.

mediumBOSS.jpgMe.dium captures 20m URLs daily and will use BOSS to show social relevance in addition to link-weight in search. 

Does Anyone Really Care About Niche Vertical Search Engines?

We asked Yahoo! just that, although we believe that alternative search engines can be pretty exciting. None the less, we think it’s a valid question.

Senior Director of the Open Search Platform, Bill Michels told us that niche search engines often aren’t very good because they have access to a very limited index of content. It’s expensive to index the whole web. Likewise, Michels said that there are a substantial number of large organizations that have a huge amount of content but don’t have world-class search technology.

In both cases, Yahoo! BOSS is intended to level the playing field and blow the Big 3 wide open. We agree that it’s very exciting to imagine thousands of new Yahoo! powered niche search engines proliferating. Could Yahoo! plus the respective strengths and communities of all these new players challenge Google? We think they could.

Hakia will parse the Yahoo! index for semantic meaning and data type.–>

What’s Not Included?

The BOSS APIs are in beta for now, so they may be expanded with time – but for now there are still a few crown jewels in the company’s plans that won’t be opened up. We asked about Yahoo’s indexing of the semantic web and were told that would not be a part of BOSS. We asked about the Inbox 2.0 strategy and the company’s plans to rewire for social graph and data portability paradigms. We were told that those were “other programs.”

We hope that there’s not a fundamental disconnect there that will lead to lost opportunities and a lack of focus. It is clear, though, that BOSS falls well within the company’s overall technical strategy of openness. When it comes to web standards, openness and support for the ecosystem of innovation – there may be no other major vendor online as strong as Yahoo! is today. These are times of openness, where some believe that no single vendor’s technology and genius alone can match the creativity of an empowered open market of developers. Yahoo! is positioning itself as leader of this movement.

Let’s see what they can do with an army of Yahoo! powered search engines. Let the games begin!

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Is Google a Semantic Search Engine?

Written by Guest Author / March 26, 2007 1:00 PM / 35 Comments

Written by Phill Midwinter, a search engineer from the UK. This is a great follow-up to our article last Friday, Hakia Takes On Google With Semantic Technologies.

What is a Semantic Engine?

Semantics are said to be ‚Äòthe next big thing‚Äô in search engine technology. We technology bloggers routinely drum up articles about it and sell it to you, the adoring masses, as a product that will change your web experience forever. Problem is, we often forget to tell you exactly what semantics are – we just get so excited. So let’s explore this…

Wikipedia says:

‚ÄúSemantics (Greek semantikos, giving signs, significant, symptomatic, from sema, sign) refers to the aspects of meaning that are expressed in a language, code, or other form of representation. Semantics is contrasted with two other aspects of meaningful expression, namely, syntax, the construction of complex signs from simpler signs, and pragmatics, the practical use of signs by agents or communities of interpretation in particular circumstances and contexts. By the usual convention that calls a study or a theory by the name of its subject matter, semantics may also denote the theoretical study of meaning in systems of signs.‚Ä?

…which is absolutely no help.

Semantics as it relates to our topic, search engines, actually covers a few closely related fields. In this instance what we are looking at deciphering (as a basic example) is whether a computer can discern if there is a link between two words, such as cat and dog. You and I both know that cats and dogs are common household pets, and can be categorized as such. The human brain seems to comprehend this easily, but for a computer it is a much more complex task and one I won‚Äôt go into here – because it would most likely bore you.

If we take as read then, that the search engine now has semantic functionality, how does that enable it to refine its search capability?

  • It can automatically place pages into dynamic categories, or tag them without human intervention. Knowing what topic a page relates to is invaluable for returning relevant results.
  • It can offer related topics and keywords to help you narrow your search successfully. With a keyword like sport the engine would offer you a list of sports perhaps as well as sports related news and blogs.
  • Instead of offering you the related keywords, the engine can directly incorporate them back into the search with less weight than the user inputted ones. It‚Äôs still contested as to whether this will produce better results or just more varied ones.
  • If the engine uses statistical analysis to retrieve it‚Äôs semantic matches to a keyword (as Google is likely to do) then its likely that keywords currently associated with hot news topics will bring those in as well. For example, using my engine to search for the keyword police, brought up peerages (relating to the uk‚Äôs cash for honors scandal recently).

So, according to me:

‚ÄúA semantic search engine is a search engine that takes the sense of a word as a factor in its ranking algorithm or offers the user a choice as to the sense of a word or phrase.‚Ä?

This is not in line with the purists of what is known as ‘The Semantic Web’, who believe that for some reason we should spend all our time tagging documents, pages and images to make them acceptable for a computer to read. Well, I’m sorry but I’m not going to waste my time tagging when a computer is able to derive context and do it for me. I may have offended Tim Berners Lee by saying this, but as the creator of the Web he should know better.

How does Google match up?

Until extremely recently, Google‚Äôs semantic technology (which they‚Äôve had now for quite a while) was limited to matching those adsense blocks to your website‚Äôs content. This is neat, and a good practical example of the technology – but not relevant to their core search product. However if you make a single keyword search today, chances are you may spot a block like this at the bottom of your results page:

This is more or less exactly what I was just writing about. They’re offering you alternatives based upon your initial search, which in this case was obviously for citizen. Citizen is a bank, a watchmaker and (if I’m not mistaken) it means you’re a member of a country or something. This is the first clear example of Google employing a semantic engine that works by analyzing the context of words in their index and returning likely matches for sense.

Some of you may be wondering why they aren’t doing this for multiple keyword phrases, which I can take a guess at from some of my own work. Analyzing the context of a word statistically is intensive and slow; and if you try and analyze two, you slow the process further and so on. It is likely they have problems doing so for more than one keyword currently, and Google as ever is cautious about changing their interface too radically too quickly. This implementation of semantics gives hope that they haven’t adopted the purist view of ‘The Semantic Web’ where everything is tagged and filed neatly into nice little packages.

Google is all too aware of the following very large problems with that idea:

  • Users are stupid.
  • Users are lazy.
  • Redefining the way they‚Äôve indexed what is assumed to be petabytes of data would require them to effectively start again.
  • It‚Äôs not as powerful or dynamic.

How Google can utilize Semantic technologies

It’s my belief that Google will increasingly tie this technology into their core search experience as it improves in speed and reliability. It has some phenomenally powerful uses and I’ve taken the liberty of laying out a few of my suggestions on where they can go with this:

Self aware pages

  • Tagging pages with keywords has always been used on the internet to let search engines know what kind content the page contains.
  • Using a Google API we can generate the necessary keywords on the fly as the page loads. This cuts out a large amount of work for SEO.
  • A Google API enabled engine wouldn‚Äôt even need to look at these keywords, it could generate them itself.
  • Not only a page can be self aware these days, people tag everything – including links. The Google API could conceivably be used to tag every single word on a page, creating a page that covers every single keyword possibility. This is overkill – but a demonstration of the power available.

Narrow Search

  • When you begin a search, you enter just one or two keywords in the topic you‚Äôre interested in.
  • Related keywords appear, which you can then select from to target your search and remove any doubts about dual meanings of a word for example.
  • This step repeats every time you search, also possible is opinionated search.

Opinionated Search

  • Because of the way Google statistically finds the senses of keywords from the mass of pages in its index, what in fact it finds is the majority opinion from those pages of what the sense of a word is.
  • At the base level, you can select from the average opinion of related keywords and subjects from its entire index.
  • You can find the opinion at other levels as well though, and this is where the power comes in in terms of really targeting what the user is looking for quickly and efficiently. All the following mean that this is the first true example of social search:
    • Find the opinion over a range of dates, good for current events, modern history, changes in trends.
    • Find the opinion over areas of geography, or by domain extension (.co.uk, .com).
    • Find the opinion over a certain group of websites, or just one website in particular – compare that with another site.
    • Find the opinion not only over the above things but also subjects, topics, social and religious groups.
    • At the most ridiculous example level, you could even find what topics 18 year olds on myspace living in Leeds most talk about – but that I could probably guess. The point is that this is targeting demographics on a really unprecedented level.
  • Add the sites or web pages to your personal profile that you think most closely reflect your opinions, this data can then be taken into account in all future searches returning greater personal relevancy.


Google is using semantic technology, but is not yet a fully fledged semantic search engine. It does not use NLP (Natural Language Processing), but this is not a barrier to producing some truly web changing technology with a bit of thought and originality. NLP may well be (I hate myself for writing this) web 4.0 and semantics is web 3.0 Рthey are in fact different enough to be classified as such in my eyes and the technology Hakia is developing is certainly markedly distinct from Google’s semantic efforts.

There are barriers that Google needs to overcome… is it capable of becoming fully semantic without modifying it‚Äôs index too drastically; can Google continue to keep the results simple and navigable for its varied user base? Most importantly, does Google intend to become a fully semantic search engine and to do so within a timescale that won‚Äôt damage their position and reputation? I like to think that although the dragon is sleeping, that doesn‚Äôt mean it‚Äôs not dreaming!

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Deconstructing Real Google Searches: Why Powerset Matters

Written by Guest Author / January 9, 2008 1:07 AM / 13 Comments

This is a guest post by Nitin Karandikar, author of the Software Abstractions blog.

Recently I was looking at the log files for my blog, as I regularly do, and I was suddenly struck by the variety of search queries in Google from which users were being referred to my posts. I write often about the different varieties of search – including vertical search, parametric search, semantic search, and so on – so users with queries about search often land on my blog. But do they always find what they’re looking for?

All the major search engines currently rely on the proximity of keywords and search terms to match results. But that approach can be misleading, causing the search engine to systematically produce incorrect results under certain conditions.

To demonstrate, let us take a look at three general use cases.

[Note: The examples given below are all drawn from Google. To be fair, all the major search engines use similar algorithms, and all suffer from similar problems. For its part, Google handles billions of queries every day, usually very competently. As the reigning market leader, though, Google is the obvious target – it goes with the territory!]

1. Difficulty in Finding Long Tail Results

Take Britney Spears. Given the current popularity of articles, news, pictures, and videos of the superstar singer, the results for practically any query with the word “spears” in it will be loaded with matches about her – especially if the search involves television or entertainment in any way.

Let’s say you’re watching the movie Zulu and you start wondering what material the large spears that all the extras are waving about are made of. So, you go to Google and type in “movie spears material” – this is an obviously insufficient description, as the screen shot below shows.

What happens if you expand on the query further – say: “what are movie spears made out of?” – does it help?

The general issue here is that articles about very popular subjects accumulate high levels of PageRank and then totally overwhelm long tail results. This makes it very difficult for a user to find information about unusual topics that happen to lie near these subjects (at least based on keywords).

2. Keyword Ordering

Since the major search engines focus only on the proximity of keywords without context, a user search that’s similar to a popular concept gets swamped with those results, even if the order of keywords in the query has been reversed. For example, a tragic occurrence that’s common in modern life is that of a bicycle getting hit by a car. Much less common is the possibility of a car getting hit by a bicycle, although it does happen. How would you search for the latter? Try typing “car hit by bicycle” into Google; here’s a screen shot of what you get. [Note the third result, which is actually relevant to this search!]

3. Keyword Relationships

Since the major search engines focus only on the keywords in the search phrase, all sense of the relationship between the search terms is lost. For example, users commonly change the meaning of search terms by using negations and prepositions; it is also fairly common to look for the less common members of a set.

This takes us into the realm of natural language processing (NLP). Without NLP, the nuances of these query modifications are totally invisible to the search algorithms.

For example, a query such as “Famous science fiction writers other than Isaac Asimov” is doomed to failure. A screen shot of this search in Google is presented below. Most of the returned results are about Isaac Asimov, even when the user is explicitly trying to exclude him from the list of authors found.

All of the searches shown above look like gimmicks – queries designed intentionally to mislead Google’s search algorithms. And in a sense, they are; these specific queries can be easily fixed by tweaking the search engine. Nevertheless, they do point to a real need: the value of understanding the meaning behind both the query and the content indexed.

Semantic Search

That’s where the concept of semantic search comes in. I attended a media event earlier this year at stealth search startup Powerset (see: Powerset is Not a Google-killer!), at which they showcased a live demo of their search engine, currently in closed alpha, that highlighted solutions to exactly this type of issue.

For example, type “What was said about Jesus” into a major search engine, and you usually get a whole list of results that consist of the teachings of Jesus; this means that the search engine entirely missed the concepts of passive voice and “about.” The Powerset results, on the other hand, were consistently on target (for the demo, anyway!).

In other words, when you look at just the keywords in the query, you don’t really understand what the user is looking for; by looking at them within context, by taking into account the qualifiers, the prepositions, the negatives, and other such nuances, you can create a semantic graph of the query. The same case can be made for semantic parsing of the content indexed. Put the two together, as Powerset does, and you can get a much better feel for relevance of results.

What about Google? I’m sure the smart folks in Google’s search-quality team are busily working on this problem as well. I look forward to the time when the major search engines handle long tail queries more accurately and make search a better experience for all of us.

Update: for an expanded version of this article with real-life user queries, see my blog.

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Google’s US Search Market Dominance Hits All Time High

Written by Marshall Kirkpatrick / April 7, 2008 1:51 PM / 15 Comments

Traffic analysts Hitwise released new numbers today finding that Google’s marketshare in US searches rose last month to an all time high of 67% of searches performed. Yahoo! Search (20%), MSN Search (5.25%) and Ask.com (4%) trail far behind but aren’t insignificant either.

At this time last year Google was at 64% and MSN was at 9%. Momentum remains with Google, but is that momentum inevitable? Could things change? We’ve written about three ways that it could.


Some have argued that Google’s approach to search is outdated and slow to change. Apparently it’s working just fine for them today, but there’s a world of opportunities for other innovators to come up with a better search experience. We wrote about this situation in our recent post titled “How Vulnerable is Google in Search?

Hitwise tracks 46 other search engines as well, which added up for a combined 1.7% of searches last month. 46 alternative search engines is like a week’s work for our network blog AltSearchEgines, check it out if you’d like to learn about the rest of the industry, including some that may become the challengers of the future.

Semantic Web

Yahoo! is #2 today, but is taking the lead in support for standards based microformats and semantic web indexing. Yahoo! announced that it would index semantic markup three weeks ago. Since semantic markup could enable improvements in search quality by orders of magnitude, this could be a turning point for Google and Yahoo!

As we explained when that announcement was made:

Today, a web service might work very hard to scour the internet to discover all the book reviews written on various sites, by friends of mine, who live in Europe. That would be so hard that no one would probably try it. The suite of technologies Yahoo! is moving to support will make such searches trivial. Once publishers start including things like hReview, FOAF and geoRSS in their content then Yahoo!, and other sites leveraging Yahoo! search results, will be able to ask easily what it is we want to do with those book reviews. Say hello to a new level of innovation.


We’d like to get an update on the Yahoo! semantic indexing announcement, though, and presumably this is the kind of thing that Google will do soon as well.

Privacy Backlash

As Google grows continually stronger and more knowledgeable, the importance of the social contract between the company and its customers becomes increasingly more important. Google has not been as good as it needs to be about taking clear steps to guarantee security and prevent misuse of user data – including its own misuse of that data!

We wrote in February about how Microsoft’s new levels of engagement with oppenness and data portability could offer an avenue to challenge Google, but few of our readers agreed in comments. You know what they say, though – if your mouth gets washed out with soap, you may be saying something important!

It may not be Microsoft that challenges Google, but it certainly seems possible that users will draw the line somewhere and look to limit Google’s omniscience.

Perhaps not, though. Perhaps Google’s search dominance will continue to grow and grow, month over month, year over year. Someday, if you want to know about your genetic propensity for a particular disease, you’ll just as the Google. If you want to know what your kids are doing at home while you’re away, you’ll just ask the Google. Certainly today when we want to know what’s on the web, a clear majority of us just ask the Google.


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How Vulnerable is Google on Search?

Written by Marshall Kirkpatrick / February 21, 2008 10:45 AM / 22 Comments

A new wrinkle in the search landscape emerged this morning with the announcement that Ask.com is now offering Compete traffic stats inline for the sites on results pages. (Disclosure: Compete is an RWW advertiser.) This move itself may not shake up search but it does beg the question, how much room for meaningful innovation is there in search and to what degree is Google vulnerable in the market it so dominates?

Ask.com comes up with interesting features all the time that tend not to get a big reaction. This move’s impact is mitigated by the facts that Compete traffic data is limited to US site visitors and the stats aren’t yet available on Ask’s fantastic blog search. None the less, I think it’s an interesting case that demonstrates just how open the future of search remains.

In addition to offering value adds like traffic data, search by semantic or natural language meaning is an option for search that’s widely discussed. Social search is yet another. Researchers at Stanford posted an interesting study this week on the role social bookmarking could play in augmenting search.

On Google

I find myself consistently impressed with a lot of what Google does but the fact remains that Google web search isn’t changing much. They are folding all the various search engines into one, but the experience isn’t changing dramatically. Does it need to? Check out this rant below from Doc Searls, on recent episode of the excellent NewsGang Podcast. Searls calls Google, “the Windows of search.”

I think Google is vulnerable in search. Google hasn’t changed search in 7 or 8 years, they are fat and happy. There are so many ways search can be improved. Google is way too locked into Larry and Sergey’s original vision, which has hardly changed at all; it’s not the only cannonical way to do search. There’s so many ways to granulate search and make it conditional and do a much better job. Google’s search is lame in a lot of ways, it’s very minimal – it’s just become common but that doesn’t mean it’s perfect. It is the Windows of search.There’s a huge vulnerability there. I was talking to someone who used to work at Google who said that the reason Google Blogsearch has been moribund for years…is because Larry thinks that Google ought to have one search experience and that search experience should never change. Since Larry wants it that way, Google Blogsearch is just sitting there and may actually go away. It’s inexcusable, I don’t care how much research they are doing – they are blowing smoke up their own ass if they think that there is only one good experience we can have with search. It is not enough. There is enormous room for other people to compete with that…Get out of your shell where you think the whole world is these companies and what they bring to the table now.


Ask’s integration with Compete is just one small example of what’s possible. Searls doesn’t take into consideration Google’s mindshare in the passage above but I agree with the basic premise that some major new feature, algorithm or user experience could prove very compelling for searchers at large. Here at the ReadWriteWeb network, we’ve got a whole blog about alternative search engines.

Google isn’t the most lovable brand in the world and no one can be the coolest cat in school forever.

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Semantic Travel Search Engine UpTake Launches

Written by Josh Catone / May 14, 2008 6:00 AM / 8 Comments

According to a comScore study done last year, booking travel over the Internet has become something of a nightmare for people. It’s not that using any of the booking engines is difficult, it’s just that there is so much information out there that planning a vacation is overwhelming. According to the comScore study, the average online vacation plan comes together through 12 travel-related searches and visits to 22 different web sites over the course of 29 days. Semantic search startup UpTake (formerly Kango) aims to make that process easier.

UpTake is a vertical search engine that has assembled what it says is the largest database of US hotels and activities — over 400,000 of them — from more than 1,000 different travel sites. Using a top-down approach, UpTake looks at its database of over 20 million reviews, opinions, and descriptions of hotels and activities in the US and semantically extracts information about those destinations. You can think of it as Metacritic for the travel vertical, but rather than just arriving at an aggregate rating (which it does), UpTake also attempts to figure out some basic concepts about a hotel or activity based on what it learns from the information it reads. Things such as, is the hotel family friendly, would it be good for a romantic getaway, is it eco friendly, etc.

“UpTake matches a traveler with the most useful reviews, photos, etc. for the most relevant hotels and activities through attribute and sentiment analysis of reviews and other text, the analysis is guided by our travel ontology to extract weighted meta-tags,” said President Yen Lee, who was co-founder of the CitySearch San Francisco office and a former GM of Travel at Yahoo!

What UpTake isn’t, is a booking engine like Expedia, a meta price search engine like Kayak, or a travel community. UpTake is strictly about aggregation of reviews and semantic analysis and doesn’t actually do any booking. According to the company only 14% of travel searches start at a booking engine, which indicates that people are generally more interested in doing research about a destination before trying to locate the best prices. Many listings on the site have a “Check Rates” button, however, which gets hotel rates from third party partner sites — that’s actually how UpTake plans to make money.

The way UpTake works is by applying its specially created travel ontology, which contains concepts, relationships between those concepts, and rules about how they fit together, to the 20 million reviews in its database. The ontology allows UpTake to extract meaning from structured or semi-structured data by telling their search engine things like “a pool is a type of hotel amenity and kids like pools.” That means hotels with pools score some points when evaluating if a hotel is “kid friendly.” The ontology also knows, though, that a nude pool might be inappropriate for kids, and thus that would take points away when evaluating for kid friendliness.

A simplified example ontology is depicted below.

In addition to figuring out where destinations fit into vacation themes — like romantic getaway, family vacation, girls getaway, or outdoor — the site also does sentiment matching to determine if users liked a particular hotel or activity. The search engine looks for sentiment words such as “like,” “love,” “hate,” “cramped,” or “good view,” and knows what they mean and how they relate to the theme of the hotel and how people felt about it. It figures that information into the score it assigns each destination.


Yesterday, we looked at semantic, natural language processing search engine Powerset and found in some quick early testing that the results weren’t that much different than Google. “If Google remains ‘good enough,’ Powerset will have a hard time convincing people to switch,” we wrote. But while semantic search may feel rather clunky for the broader global web, it makes a lot of sense in specific verticals. The ontology is a lot more focused and the site also isn’t trying to answer specific questions, but rather attempting to semantically determine general concepts, such as romanticness or overall quality. The upshot is that the results are tangible and useful.

I asked Yen Lee what UpTake thought about the top-down vs. the traditional bottom-up approach. Lee told me that he thinks the top-down approach is a great way to lead into the bottom-up Semantic Web. Lee thinks that top-down efforts to derive meaning from unstructured and semi-structured data, as well as efforts such as Yahoo!’s move to index semantic markup, will provide an incentive for content publishers to start using semantic markup on their data. Lee said that many of UpTake’s partners have already begun to ask how to make it easier for the site to read and understand their content.

Vertical search engines like UpTake might also provide the consumer face for the Semantic Web that can help sell it to consumers. Being able to search millions of reviews and opinions and have a computer understand how they relate to the type of vacation you want to take is the sort of palpable evidence needed to sell the Semantic Web idea. As these technologies get better, and data becomes more structured, then we might see NLP search engines like Powerset start to come up with better results than Google (though don’t think for a minute that Google would sit idly by and let that happen…).

What do you think of UpTake? Let us know int he comments below.

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Hakia Takes On Google With Semantic Technologies

Written by Richard MacManus / March 23, 2007 12:14 PM / 17 Comments

This week I spoke to Hakia founder and CEO Dr. Riza C. Berkan and COO Melek Pulatkonak. Hakia is one of the more promising Alt Search Engines around, with a focus on natural language processing methods to try and deliver ‘meaningful’ search results. Alex Iskold profiled Hakia for R/WW at the beginning of December and he concluded, after a number of search experiments, that Hakia was intriguing – but it was not a level to compete with Google yet. It is important to note that Hakia is a relatively early beta product and is still in development. But given the speed of Internet time, 3.5 months is probably a good time to check back and see how Hakia is progressing…

What is Hakia?

Riza and Melek firstly told me what makes Hakia different from Google. Hakia attempts to analyze the concept of a search query, in particular by doing sentence analysis. Most other major search engines, including Google, analyze keywords. Riza and Melek told me that the future of search engines will go beyond keyword analysis – search engines will talk back to you and in effect become your search assistant. 

One point worth noting here is that, currently, Hakia still has some human post-editing going on – so it isn’t 100% computer powered at this point.

Hakia has two main technologies:

1) QDEX Infrastructure (which stands for Query Detection and Extraction)  – this does the heavy lifting of analyzing search queries at a sentence level.

2) SemanticRank Algorithm – this is essentially the science they use, made up of ontological semantics that relate concepts to each other.

If you’re interested in the tech aspects, also check out hakia-Lab – which features their latest technology R&D.

How is Hakia different from Ask.com?

Hakia most reminds me of Ask.com, which uses more a natural language approach than the other big search engines (‘ask’ a question, get an answer) – and also Ask.com uses human editing too, as with Hakia. [I interviewed Ask.com back in November]. So I asked Riza and Melek what is the difference between Hakia and Ask.com?

Riza told me that Ask.com is an indexing search engine and it has no semantic analysis. Going one step below, he says to look at the basis of their results. Ask.com bolds keywords (i.e. it works at a keywords level), whereas Riza said that Hakia understands the sentence. He also said that Ask.com categories are not meaning-based – they are “canned or prefixed”. Hakia, he said, understands the semantic relationships.

Hakia vs Google

I next referred Riza and Melek to Read/WriteWeb’s interview with Matt Cutts of Google, in which Matt told me that Google is essentially already using semantic technologies, because the sheer amount of data that Google has “really does help us understand the meanings of words and synonyms”. Riza’s view on that is that Google works with popularity algorithms and so it can “never have enough statistical material to handle the Long Tail”. He says a search engine has to understand the language, in order to properly serve the Long Tail.

Moreover, Hakia’s view is that the vastness of data that Google has doesn’t solve the semantic problem – Riza and Melek think there needs to be that semantic connection present.

Their bigger claim though is that the big search companies are still thinking within an indexing framework (personalization etc). Hakia thinks that indexing has plateaued and that semantic technologies will take over for the next generation of search. They say that semantic technologies allow you to analyze content, which they think is ‘outside the box’ of what the big search companies are doing. Riza admitted that it was possible Google was investigating semantic technologies, behind closed doors. Nevertheless, he was adamant that the future is understanding info, not merely finding it – which he said is a very difficult problem to solve, but it’s Hakia’s mission.

Semantic web and Tim Berners-Lee

Throughout the interview, I noticed the word “semantic” was being used a lot – but their interpretation seemed to be different to that of Tim Berners-Lee, whose notion of a Semantic Web is generally what Web people think about when uttering the ‘S’ word. Riza confirmed that their concept of semantic technology is indeed different. He said that Tim Berners-Lee is banking on certain standards being accepted by web authors and writers – which Riza said is “such a big assumption to start this technology”. He said that it forces people to be linguists, which is not a common skill.

Furthermore, Riza told me that Berners-Lee’s Semantic Web is about “imposing a structure that assumes people will obey [and] follow”. He said that the “entire Semantic Web concept relies on utilizing semantic tagging, or labeling, which requires people to know it.” Hakia, he said, doesn’t depend on such structures. Hakia is all about analyzing the normal language of people – so a web author “doesn’t need to mess with that”.


Apart from Google and the other big ‘indexing’ search engines, Hakia is competing against other semantic search engines like Powerset and hybrids like Wikia. Perhaps also Freebase – although Riza thinks the latter may be “old semantic web” (but he says there’s not enough information about it to say for sure).


Hakia plans to launch its version 1.0 (i.e. get out of beta) by the end of 2007. As of now my assessment is the same as Alex’s was in December – it’s a very promising, but as yet largely unproven, technology.

I also suspect that Google is much more advanced in search technology than Mountain View is letting on. We know that Google’s scale is a huge advantage, but their experiments with things like personalization and structured data (Google Base) show me that Google is also well aware of the need to implement next-generation search technologies. Also, as Riza noted during the interview, who knows what Google is doing behind closed doors.

Will semantic technologies and ‘sentence analysis’ be the next wave of search? It seems very plausible. So with a bit more development, Hakia could well become compelling to a mass market. Therefore how and when Google responds to Hakia will be something to watch carefully.

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Report: Semantic Web Companies Are, or Will Soon Begin, Making Money

Written by Marshall Kirkpatrick / October 3, 2008 5:13 PM / 14 Comments

provostpic-1.jpgSemantic Web entrepreneur David Provost has published a report about the state of business in the Semantic Web and it’s a good read for anyone interested in the sector. It’s titled On the Cusp: A Global Review of the Semantic Web Industry. We also mentioned it in our post Where Are All The RDF-based Semantic Web Apps?.

The Semantic Web is a collection of technologies that makes the meaning of content online understandable by machines. After surveying 17 Semantic Web companies, Provost concludes that Semantic science is being productized, differentiated, invested in by mainstream players and increasingly sought after in the business world.

Provost aims to use real-world examples to articulate the value proposition of the Semantic Web in accessible, non-technical language. That there are enough examples available for him to do this is great. His conclusions don’t always seem as well supported by his evidence as he’d like – but the profiles he writes of 17 Semantic Web companies are very interesting to read.

What are these companies doing? Provost writes:

“..some companies are beginning to focus on specific uses of Semantic technology to create solutions in areas like knowledge management, risk management, content management and more. This is a key development in the Semantic Web industry because until fairly recently, most vendors simply sold development tools.”


The report surveys companies ranging from the innovative but unlaunched Anzo for Excel from Cambridge Semantics, to well-known big players like Down Jones Client Solutions and RWW sponsor Reuters Calais Initiative, to relatively unknown big players like the already very commercialized Expert System. 10 of the companies were from the US, 6 from Europe and 1 from South Korea.

semwebchart.jpgAbove: Chart from Provost’s report.We’ve been wanting to learn more about “under the radar” but commercialized semantic web companies ever since doing a briefing with Expert System a few months ago. We had never heard of the Italian company before, but they believe they already have they have a richer, deeper semantic index than anyone else online. They told us their database at the time contained 350k English words and 2.8m relationships between them. including geographic representations. They power Microsoft’s spell checker and the Natural Language Processing (NLP) in the Blackberry. They also sell NLP software to the US military and Department of Homeland Security, which didn’t seem like anything to brag about to us but presumably makes up a significant part of the $12 million+ in revenue they told Provost they made last year.

And some people say the Semantic Web only exists inside the laboratories of Web 3.0 eggheads!

Shortcomings of the Report

Provost writes that “the vendors [in] this report have all the appearances of thriving, emerging technology companies and they have shown their readiness to cross borders, continents, and oceans to reach customers.” You’d think they turned water into wine. Those are strong words for a study in which only 4 of 17 companies were willing to report their revenue and several hadn’t launched products yet.

The logic here is sometimes pretty amazing.

The above examples [there were two discussed – RWW] are just a brief sampling of the commercial success that the Semantic Web has been experiencing. In broad terms, it’s easy to point out the longevity of many companies in this industry and use that as a proxy for commercial success [wow – RWW]. With more time (and space in this report), additional examples could be described but the most interesting prospect pertains to what the industry landscape will look like in twelve months. [hmmm…-RWW]


In fact, while Provost has glowingly positive things to about all the companies he surveyed, the absence of engagement with any of their shortcomings makes the report read more like marketing material than any objective take on what’s supposed to be world-changing technology.

This is a Fun Read

The fact is, though, that Provost writes a great introduction to many companies working to sell software in a field still too widely believed to be ephemeral. The stories of each of the 17 companies profiled are fun to read and many of Provost’s points of analysis are both intuitive and thought provoking.

He says the sector is “on the cusp” of major penetration into existing markets currently served by non-semantic software. Provost argues that the Semantic Web struggles to explain itself because the World Wide Web is so intensely visual and semantics are not. He says that reselling business partners in specific distribution channels are combining their domain knowledge with the science of the software developers to bring these tools to market. He tells a great, if unattributed, story about what Linked Data could mean to the banking industry.

We hadn’t heard of several of the companies profiled in the report, and a handful of them had never been mentioned by the 34 semantic web specialist blogs we track, either.

There’s something here for everyone. You can read the full report here.

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