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Presumably the current SERPs returned by Google would have pages that would have incorporated Hillary Clintons response on Health Care
A general query would probably return web pages encompassing virtually all high profile liberal Democrats
Once the technology is released to the public and there are meaningful results, I will be the first in line to try it out and listen to customer reactions, but it seems a bit premature to knock a few points off of Google's stock price.
:)
That said, as "great" as Google's results are now, I have no doubt that in a few years, people will look back and think about how primitive the page rank idea is.
Though, like Powerset’s, paid match is not yet an operating system, our own US Dept of Labor does run a very popular service (over 500,000 users/month) which provides an enlightening and instructive peak at the potential that such a paid match search/ad platform possesses.
Called GovBenefits (available at govbenefits.gov), it utilizes a personal profile and a match engine to determine what government benefit programs people qualify for.
Were such a system populated with the 100's of thousands to millions of products and services companies provide nation/worldwide instead of just the 400-odd government programs it includes now, one can only imagine what its public popularity would be...
...and with the world’s advertisers having the ability to pinpoint target and control; via bidding directly on those keytraits most relevant and applicable to their products and services, exactly who sees their ads (goodbye click fraud); one can also only imagine the deleterious effects that such an elegant and superior system/platform would have on a 95% PPC income dependent company like Google...
I didn't know IBM was acquired.
Or what's the difference between my company acquiring a Computer from IBM and and somebody else acquiring a business unit?
Now if I make up an article about my company acquiring IBM, will this article turn up as a result. Page Ranking would maybe list it as the 1m link, since nobody will believe it and link to it.
In other words NLP without shared context is just random sentences used in a conversation. Or you have a lot of explaining to do about what you mean and what you trust. Or, for a right wing nut, liberal has a totally different meaning then for a left wing nut. So while Page Rank includes some of the wisdom of the crowd how does NLP do that. Language is very subjective.
In other words your client system has share your context with the server, if you want to stay sane and get some things done. But we are are a few years away from pretty pictures in the UI to context driven machines. But less then 5 years if somebody would ask me, nobody does by the way. Don't know why :-).
Personally, I'd like to see a market for elite managed directories that those listed pay to participate in with an account manager handling a couple hundred sites...all of which are highly relevant and vetted for a particular niche. A hundred such niches in a directory that a business or journalist could subscribe to and get quality content, answers, and results that would serve not only as quality research but even immediately actionable intelligence would be kind of cool.
Combine that with Yahoo! Pipes and you could make for a powerful model. The problem isn't with search technology so much as it is with content quality. While it might sound a bit retro, I wouldn't mind seeing a return of edited directories combined with the new NL technology. I'd pay a subscription fee for vetted results, and depend on Piped data that met very specific requirements for outside information and news from XML feeds.
Some day when Google bombs are gone, I might buy into the notion that search is anything to lose sleep over. Word of mouth and social networking are still more intriguing than search to me, perhaps because I still put more creedence in WOM than any other marketing tool. Pipes might help change the status quo for mining data effectively from RSS feeds. So might this NL effort by Powerset do the same for search. I won't hold my breath hoping.
Anyway...great post.
Propel it past Google in what way? In that they deliver better results? In that they'll have more users? In that they'll make more money?
I could say that MSN has better search relevancy than Google, but does that mean everyone's going to switch tomorrow?
Google is a powerhouse because of their advertising. Their search relevancy is just good enough. What sort of money printing machine is Powerset building? There's no mention of it.
Ronald's point about shared context is extremely relevant. I would say Google's answer to this is personalized search. It's just in its infancy, but it's a start. I would say at least, or probably more important in maintaining users is establishing that relationship. How long will it take to establish a relationship with Powerset, so it understands what the heck you're asking it? What's in it for users to give it that chance?
The next and final (post Google/Powerset) achievement in breakthrough user experience will be Jarg Corporation’s Semantic Knowledge Indexing Platform (SKIP) launch mastering "NOP" Natural Object Parsing that co-populates "well-understood native object content fragments" in the same master index with NLP-graph fragments. This final step - using conversational style requests (over a cell phone or keyboard) will provide total information awareness associated with the "roll" of the user - as derived on the fly from the full context of the request's information needs. Only relevant knowledge will be considered and the more contexts in the request - the more highly personalized will be the returns-ranking. These returns will be a “collage,†ranked by fit-to-context, of image segments, fragrances, text, structure segments, music segments and all forms of knowledge with precise contextual relation to your on the fly the needs – fit to your “user’s roll†of the moment. Jarg will be seeking its very fist institutional capital starting in March 2007. Jarg has incorporated Semantx Life Science, Inc. Care Commons, Inc and Preemptive Alert Corporation to become best of breed in their verticals.
From the experience most end users put 2-3 keywords inside the search box.
Of course being taken to the exact page was the result of entering a very specific query. I had entered a fairly long list of query terms each of which have pretty low frequency in the total web content. (And of course I was lucky that that page did in fact exist).
To me the value in search is finding the one single page that has the exact detail you are looking for. In my example above, this occurred because of the number of explicit search terms I had entered. But most often, I have to manually search through many pages until either I find what I am looking for.
Eventually search capabilities will improve to give users more targeted search results. By targeted, I mean a better threshold for what is relevant to the query than just "this page contains the words you asked for". Eventually the search threshold will be "this page contains the MEANING you asked for".
In time, linguistics will be applied to help improve search capabilities. Things like word-sense disambiguation, word synonyms and sentence structure will likely all play in this.
I believe in what the above person says. That has been the major bottleneck when developing any NLU engine. I myself had developed a NL Interface to Operating System sometime back, it worked correctly till Users started expecting more and the minor mismatches were blown out thus reducing the confidence of people in the System.
Regarding the hype of PowerSet and the NLP technology they are developing, it is not that new!
At Bitext, we have been developing natural language search engines for more than 4 years now. These engines allow users to query in natural language to any computer application, including the web.
If you would like to see how it works, you can visit our demo of NaturalFinder integrated with MSN Search for English at http://demos.bitext.com/MSNen/frames.htm
Our technology can be easily integrated with any search engine like Google Search Appliance, Autonomy, dtSearch, Lucene, etc.
For more info, do not hesitate to contact us!
Good day to all!
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Now take an example of the Machine translation system by the Google (specifically I will talk of English to Hindi), its statistical but doesn't do any sensible translation. On other hand you can see a English to Hindi machine translation system called MaTra doing much better than it. You can try this here
http://202.141.152.9/matra/index.jsp . This seems to be much better than Google's. And so I think guys at Google shouldn't Ignore the other growing giants, as today only I read Dianosor vanish one day...!
You will be successful.