Feed: Comments for 2008 Web Predictions - AggScore: 56.6

Semantic Search: The Myth and Reality

Comment from James Kelway on 2008-06-19

Alex,

I'm really glad you wrote this article and it has sparked off a few things in my mind that I have thought about for a while.

I would disagree with the comment of debunking, mentioned above. Any way of making us think differently about the accepted paradigms of what a search interface should look like is welcome in my book. Of course my experience of technologies is limited but perhaps in this case thats a good thing.

The post here http://userpathways.com/2008/06/18/the-answer-is-in-the-interface/ helps to explain my point of view. But I think its a valuable point you make.

Comment from Ken Ewell on 2008-06-17

I wonder if you are thinking about getting out of the industry as you are asking after a vocation, Alex. As usual I agreed with very little of what you wrote and have debunked your analysis of "semantic search" over at my blog. What was most shocking was how you generalized the performance of a few search engines and miss-characterized the nature of semantics and its role of producing more satisfying results from the search engine.

See my blog for more...

Comment from myWidowMaker on 2008-06-16

there is a strategic 1300 channel vertical locator domain platform is the greatest semantic location engine network ever created. fellas a day will come soon when we dont type in terms. all the terms (icons)will already be there. simple stuff. integration is king. search boxes are on there way out, location channels are in. got a network of location channels? if you do and it is the greatest? you just might win the game. got position?

Comment from De^min L.Igor, Russia on 2008-06-11

Wonderful article, I work the same sphere.I believe both natural & artificial languages do not allow us to open the
inner stucture of scientific info, more -matrix of scholar
studies as itself. As Mozes gave jews 10-range table there
is much more sophisticated 96-table of social thought.Inst
ead of eschelon papers on the subject You obtain just what
you need.Best wishes to You, would like to send You some materials of me. Igor.

Comment from Dan on 2008-06-09

Alex,

You asked, "what should semantic search companies do to gain their place in the market place?"

I work for a semantic search company, so I'll tell you what we're doing.

(Disclaimer: I know you're not supposed to go onto blogs and write about your company, but it's particularly germain to the question.)

1. Pick a broken vertical. Many of the semantic search companies are focused on areas where the user experience is pretty good. At Trovix, we're going after job seekers because other search technologies fail for jobs. Page rank is meaningless for job listings because they don't get linked to. Key word search is useless because the same type of job may have different titles, and the same skill set may be referred to with different words. Semantic search for jobs can show you jobs that no other search method will.

Going vertical has other advantages. You don't have to boil the ocean to build a semantic model that understands the domain it's working in. A lucrative vertical means you can get to revenue fast.

2. Change the user experience. You're totally right on this one. The Google type search box encourages a navigational search which leads to a bad experience. On most job sites, the average search string is 2.2 words. What results could possibly come back with that. At Trovix, we require people to give us their resume (500 to 1000 words) so we can build a model of who that person is, and what they might be interested in doing.

3. Deliver great results. If people have to really think to understand why one search is better than another, than Google wins. People are creatures of habit. Our objective is to provide such great results that people immediately see the difference.

Comment from DRRoth on 2008-06-04

Alex,

I was gladdened by the conclusion of your post: user experience is king. When the dust settles around this developing technology, it's utility and value will be determined 1) by the user's willingness to interact with it in a way that surfaces its advantages and 2) the interface's ability to return results that represent its utility and value at a glance.

As to the question of who is most likely to embrace the technology, I believe most of your skeptical commentors are thinking too broadly about the audience. There are many deep searchers in large international companies (e.g. think pharma) trying to leverage internal assets and business intelligence across disciplines and geographies who would gladly enter more than a simple keyword query if they believed it would improve their results and save them time.

Comment from Valentin on 2008-06-03

What you seem to be missing is any consideration for the user's willingless to learn to use these 'powerful search interfaces' - all experience shows it is close to none. In general users are not able to understand, willing to learn and motivated to use complex search interfaces.

If you entice users to ask real questions (and not use keyword queries) your facing a different problem: no algorithm in existence today is able to correctly answer even half of arbitrary worded questions, hence users will be faced with a search engine giving mostly false answers.

It is for these reasons that Semantic Search approaches only recently started to mimic the text input field of Google, pushing any fancy user interaction into the query refinement phase and thereby lowering the entrance barrier for users.

Comment from Kameir on 2008-06-03

I enjoyed reading your thoughts.
Here are my two cents:
The Semantic Web is a web of data, in some ways like a global database, characterized and relying on correct tagging of elements. This should make the work of bots much easier and allow algorithms to rely on information versus having to spend computing power on figuring out if 'apple' is a fruit or a company name.
So, the way I see it, this does not really change a whole lot about the way the data is presented (search result).
But search engines use one algorithm for every user. This approach seems to be inherently flawed. Search results should reflect reality .. in the sense, that we all have our own reality and hence our 'own' algorihtm.
It seems like Google is gradually moving into that direction ...

Comment from Joshua Drake on 2008-06-02

I gave this more complex query a try and instead found the opposite. Google was able to answer, in search position number two, the query: What cartoon involves a boy who becomes a girl? However, Powerset had no answer for me.

Additionally Google provided other series that the criteria, of which I was previously unaware.

Comment from Greg Boutin on 2008-06-02

Good job again, Alex.

I've commented in the past few weeks on my blog that the killer app powered by web semantics was most likely NOT going to be about search, and that Powerset should not try to look like a search engine. To a new technology, a new value prop. Glad the message is being amplified here.

I believe, as (for full disclosure) does my employer, that web semantics (note I'm not using the "semantic web" terminology which is too marked with a specific set of technologies) will best support a personalized knowledge ecosystem, a customized web that assembles and delivers just the data you need, in real time. When that works, we'll be able to say "SEARCH = CONTENT", since searching will really about telling the computer what you want, and having it delivered tailored-made to you based on your query and when needed an understanding of who you are.

Really looking forward to seeing the industry jump on this bandwagon!

Comment from Andrew Dalke on 2008-05-31

When I asked Google "What actor starred in both Pulp Fiction and Saturday Night Fever?", the top few answers were John Travolta, and the hits to "What two US Senators received donations from a foreign entity?" it will find your article, wherein you said "Turns out that both Barak Obama and Hillary Clinton received donations from UBS AG."

Then again, if you go to McCain's page at http://www.opensecrets.org/pres08/contrib.php?cycle=2008&cid=N00006424 you'll see that UBS contributed $93,000 to his campaign, so the information you found .. wasn't correct. At least three US Senators received money from UBS AG.

I'm not convinced that your analysis showed anything other than your enthusiasm.

Comment from Oli Rhys on 2008-05-31

What a well thought out article. Thank you.

My opinion on the matter is that it could be a white elephant of an issue. As others have pointed out, customers don't care for the details, they just want results and that is the issue for semantic searching - nobody cares.

What would make the difference is when the public learn what semantic searching could do for them. Maybe the name is wrong and it should be called AI search, but the big picture question is still, Why are we doing this?

Are we looking to topple Google or is it to find the next big thing?

Google cannot be toppled. It is like Microsoft. However, like Microsoft, Google can be made irrelevant and that is what semantic searching should do.

Think of it as a hidden tab on your browser which uses the document you are working on to find every piece of information which is relevant and presents it to you in an easy to cut / paste form.

This would in essence be a 200 word search box but it would answer the issues being highlighted in this article.

Thanks again for a very interesting article - I hope it helps encourage smarter people than me to give us the future of the internet!!

Comment from Falafulu Fisi on 2008-05-30

LSA (for search, clustering or recommendation) is solved via an algorithm called SVD (Singular Value Decomposition), and agin LSA is 2D (rows & columns) matrix.

SVD has been tensorised recently. I have seen 3D Tensor-SVD used for online sentiment monitoring. I haven't seen anyone using it for search engine yet (based on what I 've seen in the literatures), however, one cannot discount commercial applications that already adopt it. Here some analytic examples of its use:

Eigen-Trend: Trend Analysis in the Blogosphere Based on Singular Value Decompositions

A tensor higher-order singular value decomposition for integrative analysis of DNA microarray data from different studies

MPEG Video Watermarking Using Tensor Singular Value Decomposition

I believe that Eigen-Trend tool has been made available as a commercial tool. Eigen-Trend uses higher order (multidimensional) SVD or multi-linear algebra eigen decompositions.

Comment from David Holloway on 2008-05-30

Searching for multiple concepts that can be described in a variety of ways on Google (such as prior art searching in the patent world) is challenging or impossible. These searches can be more easily conducted using combinations of boolean and proximity operators in large scale commercial databases. LSA or 'semantic' search sometimes provides results that neither system retrieves, but also provides many many 'false drops' or too much noise.

LSA systems have come a long way since I first used one over 10 years ago, but still have a ways to go. I think that one of the answers is greater user control. The 'black box' system ala Google and others is fine for simple queries, but isn't nearly as powerful as a system that allows significant user interaction via a re-iterative search process.

I know that one developer at Yahoo has commented that the future lies in training the user, not enhancing the algorithm. I think that this is the quickest way to improve results. And may be part of the solution that Alex mentions above re: the searchbox problem.

Additional solutions in creative types of data visualization in both the results and input screen can enhance the process by providing a less steep learning curve for the final user.

David.