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Working prototype ready for TT searchpoint.ijs.si

Working prototype ready for TT http://searchpoint.ijs.si. Boštjan Pajntar, Marko Grobelnik. Jožef Stefan Institute. The user. Architecture o f Search. “ Cookie ”. The user inputs a precise query. The Usual Search !. Search engine provides a list of results.

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Working prototype ready for TT searchpoint.ijs.si

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  1. Working prototype ready for TT http://searchpoint.ijs.si Boštjan Pajntar, Marko Grobelnik Jožef Stefan Institute

  2. The user Architecture of Search “Cookie” • Theuserinputs a precisequery TheUsual Search! • Search engine provides a list of results • Results are returned to theuser in a ranked list

  3. The user Architecture of SearchPoint “Cookie” • The user is presented with hits and topics • Search engine provides a list of results • Results are processed by SearchPoint web service

  4. Where does SearchPoint help? • Internet Search NOT REALY ! • Specific Search Engines • Interest from a company producing corporate search engines: recommind.com • Integrating into intranet search engine over documents Accenture (big consulting company) • Talks with image selling company photo12.com

  5. Open questions • Bussines model • Licensing - How to do it? • Another model? • Prices? • How to run a company • Involve a company to sell/license the product? • Find an executive partner? • Capitalization • Slow growth? • Venture capital?

  6. Thank You! Questions?

  7. Scenarios of usage • Disambiguation of the query: • Jaguar, Cookie, Amazon, A4, … • Sub-topic profiling: • Password (recovery, protection, generator) • Existingontologies, taxonomiesprovide different context for the same data • Study of internet presence of a topic: • Cookies (More recepies than internet cookies)

  8. Ranking Space • SearchPoint visualizes several “nodes”; each relevant to some hits • Nodes are used to createrankingspace • The position of the red focus point determines the ranking

  9. Topics and Concepts • Nodes can come from different sources: • Clustering • Ontology • Simultaneous sources WORK IN PROGRESS!

  10. K-Means Clustering • Twohundred hits (title & snippet) are documents • Topics are the twelve clusters Provided by: Wikipedia

  11. Dmoz Classifier • On the input we take DMoz RDF taxonomy data • We build a classification model consisting from models for individual categories • On the output we get: • Set of most relevant categories from DMoz • Set of most relevant keywords calculated from DMoz category

  12. Search Engines • Any search engine that returns textual results can be consumed by SearchPoint • Web Search Engines: • Google, Yahoo, Microsoft Live Search, … • ProfiledWeb searches: • New York Times, Watson, … • Corporate searches: • Accenture

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