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Advance Information Retrieval Topics

Advance Information Retrieval Topics. Hassan Bashiri. Information Filtering. Agenda. Information filtering Automatic profile learning Social filtering Training Strategies. Information Access Problems. Different Each Time. Retrieval. Information Need. Data Mining. Filtering. Stable.

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Advance Information Retrieval Topics

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  1. Advance Information Retrieval Topics Hassan Bashiri

  2. Information Filtering

  3. Agenda • Information filtering • Automatic profile learning • Social filtering • Training Strategies

  4. Information Access Problems Different Each Time Retrieval Information Need Data Mining Filtering Stable Stable Different Each Time Collection

  5. Indexing and Complexity

  6. Agenda • Inverted indexes • Computational complexity

  7. An Example Postings Term Inverted File Doc 3 Doc 1 Doc 2 Doc 4 Doc 5 Doc 6 Doc 7 Doc 8 aid 0 0 0 1 0 0 0 1 4, 8 AI A all 0 1 0 1 0 1 0 0 2, 4, 6 AL back 1 0 1 0 0 0 1 0 1, 3, 7 BA B brown 1 0 1 0 1 0 1 0 1, 3, 5, 7 BR come 0 1 0 1 0 1 0 1 2, 4, 6, 8 C dog 0 0 1 0 1 0 0 0 3, 5 D fox 0 0 1 0 1 0 1 0 3, 5, 7 F good 0 1 0 1 0 1 0 1 2, 4, 6, 8 G jump 0 0 1 0 0 0 0 0 3 J lazy 1 0 1 0 1 0 1 0 1, 3, 5, 7 L men 0 1 0 1 0 0 0 1 2, 4, 8 M now 0 1 0 0 0 1 0 1 2, 6, 8 N over 1 0 1 0 1 0 1 1 1, 3, 5, 7, 8 O party 0 0 0 0 0 1 0 1 6, 8 P quick 1 0 1 0 0 0 0 0 1, 3 Q their 1 0 0 0 1 0 1 0 1, 5, 7 TH T time 0 1 0 1 0 1 0 0 2, 4, 6 TI

  8. The Finished Product Term Inverted File Postings aid 4, 8 AI A all 2, 4, 6 AL back 1, 3, 7 BA B brown 1, 3, 5, 7 BR come 2, 4, 6, 8 C dog 3, 5 D fox 3, 5, 7 F good 2, 4, 6, 8 G jump 3 J lazy 1, 3, 5, 7 L men 2, 4, 8 M now 2, 6, 8 N over 1, 3, 5, 7, 8 O party 6, 8 P quick 1, 3 Q their 1, 5, 7 TH T time 2, 4, 6 TI

  9. Cross-Language Information Retrieval

  10. Agenda • Cross-language IR • Controlled vocabulary • Automatic indexing • Free text • Evaluation • User interface design

  11. What is CLIR? Users enter their query in one language and the search engine retrieves relevant documents in other languages. English Query French Documents Retrieval System

  12. Cross-Language Text Retrieval Query Translation Document Translation Text Translation Vector Translation Controlled Vocabulary Free Text Knowledge-based Corpus-based Ontology-based Dictionary-based Term-aligned Sentence-aligned Document-aligned Unaligned Thesaurus-based Parallel Comparable 11

  13. Retrieval System Interfaces

  14. Agenda • Query interface • Selection interface • Examination interface • Document delivery

  15. Retrieval System Model User Query Formulation Detection Selection Index Examination Indexing Docs Delivery

  16. Query Formulation User Query Formulation Detection Index

  17. Starfield

  18. NLP in IR

  19. The Different Levels of Language Analysis 1-Phonetic or Phonological Level 2-Morphological Level 3-Syntactic Level 4-Semantic Level 5-Discourse Level

  20. How Information Retrieval Works Step 1: Document Processing Step 2: Query Processing Step 3: Query Matching Step 4: Ranking & Sorting

  21. Intelligent Information RetrievalorKnowledge Based IR

  22. What Is Different From IR? • IR is more concerned with words and concepts. • IIR or KBIR is more concerned about relations. • Most of IR models assume term independence. • IIR or KBIR acknowledges existence of relationships. • IR more suitable for large scale and general retrieval • IIR or KBIR more suitable for domain specific tasks.

  23. Knowledge Based IR

  24. IIR-KBIR • Expectation or Interaction With User • Objects • KB • Relation Between the objects • Reasoning • Learning • Relation Extraction

  25. Experiments in Farsi Retrieval

  26. Retrieval Models Investigated • Fuzzy Logic • MMM, Paice • Vector Space • Probabilistic, BM25 • N-Grams • Combinational

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