Fmi semtech-semantic ir-beta


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Fmi semtech-semantic ir-beta

  1. 1. Introduction to Semantic Information Retrieval<br />A formal definition of IR; Overview of common solutions; A semantic approach to IR; applied in Insemtives<br />Mar 2010<br />
  2. 2. AtanasKiryakov, CEO of Ontotext, introduces the what, why and how of semantic technologies.<br />Prof. KirilSimov defined knowledge, reasoning, knowledge storeage and reasoning systems.<br />Mariana Damova, PhD taught you how to store knowledge in ontologies. RDF was introduced. <br />Engineers work with knowledge by describing it RDF, storing in an RDF database and reason on it using OWL.<br />Mar 2010<br />#2<br />Introduction to Semantic Technologies<br />Previously on “SemanticTech. Course ...”<br />
  3. 3. Putting knowledge to use in:<br />Information Retrieval: an informal definition by example -search engines<br />We are trying to do it better in …<br />Ontotext KIM – semantic information extraction and retrieval platform<br />Insemtives (– R & D for the next generation of semantic technologies, which objective is to …<br />Introduction to Semantic Technologies<br />#3<br />Mar 2010<br />“to bridge the gap between human and <br />computational intelligence.”<br />
  4. 4. Outline<br />Information Retrieval: formal definition<br />Measure of success<br />Common approaches<br />Vector space model<br />Using knowledge for better IR<br />Understanding queries<br />Enabling users to put rich queries<br />Applying semantic IR in KIM, Insemtives<br />Introduction to Semantic Technologies<br />#4<br />Mar 2010<br />
  5. 5. Information Retrieval: the scientist’s approach<br />Introduction to Semantic Technologies<br />#5<br />Mar 2010<br />Define it formally<br />Measure the success<br /><br />Collect examples<br />Test corpus<br />Development corpus<br />Training corpus<br />Don’t overfit!<br />Learn how others do it …<br />0 ≤ F ≤ 1<br />
  6. 6. Mar 2010<br />Vector space model<br />Documents and queries and vectors<br />Simplest way: a dimension for each term<br />Simplest value: count the time the term is present<br />Compare documents by distance, compare a query to a document using the angle<br />#6<br />Introduction to Semantic Technologies<br /><ul><li>Doing it smarter – weights instead of 0 and 1; remove dimensions all together</li></li></ul><li>Doing it (slightly) smarter: TF-IDF<br />Some words are more important than others …<br />Bestprice for iPhone<br />TF.IDF ranks matcher on rarewords higher<br />Improve your vector space with previously gathered knowledge – frequency of each word in general language<br />Mar 2010<br />#7<br />Introduction to Semantic Technologies<br />
  7. 7. Doing it smarter: reduce the dimensions<br />Some words mean the same<br />Bestprice for Apple iPhone<br />Math. Formulation: the dimension vectors are not orthogonal, thus the vector space is non-uniform<br />Reduce equivalent words to a single concept  Merge the (linearly) dependent dimension vectors into one.<br />Mar 2010<br />#8<br />Introduction to Semantic Technologies<br />
  8. 8. Using knowledge for better IR<br />How do we know that two sets of terms mean the same?<br />Account for broader / narrower relations<br />Best price for smartphones<br />Query analysis Account for structure – NLP<br />Rich user interfaces<br />Introduction to Semantic Technologies<br />#9<br />Mar 2010<br />Ontologies!<br />
  9. 9. Question answering<br />Semantic solution:<br />Introduction to Semantic Technologies<br />#10<br />Mar 2010<br />
  10. 10. Relying on ontologies: cheating?<br />Mar 2010<br />#11<br />Introduction to Semantic Technologies<br />Ontologies exist!<br />Linked Data<br />Information Extraction<br />Insemtives<br />
  11. 11. Applying semantic IR in KIM, Insemtives<br />Introduction to Semantic Technologies<br />#12<br />Mar 2010<br />
  12. 12. Demonstration<br />Introduction to Semantic Technologies<br />#13<br />Mar 2010<br />
  13. 13. Demonstration – behind the scenes<br />Introduction to Semantic Technologies<br />#14<br />Mar 2010<br />
  14. 14. Demonstration – behind the scenes (cont.)<br />Introduction to Semantic Technologies<br />#15<br />Mar 2010<br />
  15. 15. Demonstration – behind the scenes (cont.)<br />Introduction to Semantic Technologies<br />#16<br />Mar 2010<br />
  16. 16. Coming up next …<br />Anton – KIM: The complete picture<br />George and Kate2– HOWTO: Information Extraction<br />Yasen – Sentiment analysis: Put user’s voice in the vector space<br />AtanasKiryakov– Behing the scenes in the RDF database<br />Introduction to Semantic Technologies<br />#17<br />Mar 2010<br />
  17. 17. Thank you!<br />Mar 2010<br />#18<br />Introduction to Semantic Technologies<br />