2. Internet Resources Discovery (IRD) Advanced Topics

3. 2 T.Sharon-A.frank Contents  Relevance Feedback  Thesaurus  Similarity Search  Collaborative Filtering  Classification/Categorization  Clustering/Mind Maps

4. 3 T.Sharon-A.frank Relevance Feedback The process of retrieving documents based on a given document or sets of documents. The user provides the SE a “feedback” on the retrieved documents. The system retrieves new documents and improves the results on it.

5. 4 T.Sharon-A.frank Relevance Feedback Relevance feedback process –it shields the user from the details of the query reformulation process. –it breaks down the whole searching task into a sequence of small steps which are easier to grasp. –it provides a controlled process designed to emphasize some terms and de-emphasize others. Two basic techniques –Query expansion addition of new terms from relevant documents. –Term re-weighting modification of term weights based on the user relevance judgment.

6. 5 T.Sharon-A.frank Example: Amazon

7. 6 T.Sharon-A.frank Thesaurus Semantic network (graph) of related terms. Can be created manually or generated automatically using statistics. Relations in the thesaurus can be weighted. Can be used to enhance and refine queries. Love Like Similar Adore 3 2 2 3

8. 7 T.Sharon-A.frank Webster

9. 8 T.Sharon-A.frank Thesaurus - example http://www.thesaurus.com Query: “can” http://thesaurus.reference.com/search?q=can http://thesaurus.reference.com/search?q=can able container toilet and many more…

10. 9 T.Sharon-A.frank Visual Thesaurus http://www.visualthesaurus.com

11. 10 T.Sharon-A.frank Visual Thesaurus

12. 11 T.Sharon-A.frank Thesaurus – Historical AltaVista Query Refinement http://www.altavista.com/

13. 12 T.Sharon-A.frank Historical AltaVista Query Refinement (cont.) http://www.altavista.com/

14. 13 T.Sharon-A.frank Similarity Search (1) Similarity: the measure of how alike two documents are. In a vector space model: how much are two document vectors close to each other. Can be done between more than two documents. Examples: –“similar page” –“more like this” = ?

15. 14 T.Sharon-A.frank Similarity Search (2)

16. 15 T.Sharon-A.frank Similarity Search (3) Http://www.amazon.com

17. 16 T.Sharon-A.frank Similarity Search (4) Http://www.excite.com

18. 17 T.Sharon-A.frank Social/Collaborative Filtering Filtering: given a large amount of data, return the data that the user wants to see. Collaborative Filtering: the process of filtering documents by determining what documents other users with similar interests and/or needs found relevant. Also called "social filtering".

19. 18 T.Sharon-A.frank Example: Amazon

20. 19 T.Sharon-A.frank Example - Eurekster

21. 20 T.Sharon-A.frank Collaborative Filtering (1) Http://www.moviefinder.com

22. 21 T.Sharon-A.frank Collaborative Filtering (2)

23. 22 T.Sharon-A.frank Classification/Categorization Classification: the process of deciding the appropriate category for a given document. Examples: –deciding to what newsgroup an article belongs to. –what folder an email message should be directed to. –what is the general topic of an essay.

24. 23 T.Sharon-A.frank Search Categorization The result documents are ordered according to categories. The searcher can select the relevant category to display the related documents. Examples: –Excite –Vivisimo/Clusty –Teoma

25. 24 T.Sharon-A.frank Clusty

26. 25 T.Sharon-A.frank Excite

27. 26 T.Sharon-A.frank Teoma

28. 27 T.Sharon-A.frank Clustering/Mind Maps Presents relevant clustering of results. User gives feedback by selecting a cluster/category to view documents. Often with graphical visualization. Examples: –Mooter –WebBrain –KartOO

29. 28 T.Sharon-A.frank Mooter

30. 29 T.Sharon-A.frank WebBrain

31. 30 T.Sharon-A.frank KartOO (1)

32. 31 T.Sharon-A.frank KartOO (2)

33. 32 T.Sharon-A.frank References http://ihelpyou.com/search-engine-chart.html http://www.infopeople.org/search/guide.html