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Alexander Gelbukh Moscow, Russia

Explore methodologies & challenges in information retrieval & natural language processing. Research, presentations, evaluations. Enhance knowledge for publications.

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Alexander Gelbukh Moscow, Russia

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  1. Alexander Gelbukh Moscow, Russia

  2. Mexico

  3. Computing Research Center (CIC), Mexico

  4. Chung-Ang University, KoreaElectronic Commerce andInternet Application Lab

  5. Special Topics in Computer ScienceAdvanced Topics in Information Retrieval Alexander Gelbukh www.Gelbukh.com

  6. Information Retrieval • In a huge amount • of poorly structured information • find the information that you need • when you don’t know exactly what you need • or can’t explain it Key concepts: • The Web • User information need • Ranking

  7. Importance • Knowledge: the main treasure of man • Web: Repository? Cemetery of information! • Natural language and multimedia information • Poorly structured, badly written • Corporate and organizational document bases • Senate speeches: Mexico • Medical data collections • Corporate memory. Microsoft knowledge base • Future: data explosion  increasing importance

  8. Perspectives • Corporations: corporate databases • Organizations: document bases • Government • European Union multilingual problem • The same in Asia • Academy • Lots of open research topics • Web topics • Computational Linguistics topics • Intelligent technologies, AI

  9. Textbook http://sunsite.dcc.uchile.cl/irbook/

  10. Contents • Introduction • Modeling • Retrieval Evaluation • Query Languages • Query Operations • Text and Multimedia Languages and Properties • Text Operations • Indexing and Searching • Parallel and Distributed IR • User Interfaces and Visualization • Multimedia IR: Models and Languages • Multimedia IR: Indexing and Searching • Searching the Web • Libraries and Bibliographical Systems • Digital Libraries

  11. Calendar • March 4 Presentation of the course • March 11 Chapter 1: Introduction. Paper presentation. • March 18 Chapter 2: Modeling. Paper presentation. • March 25 Chapter 3: Retrieval evaluation. Paper presentation. • April 1 Chapters 4-7. Paper presentation. • April 8 Chapter 8: Indexing and Searching. Paper presentation. • April 15 Chapter 9: Parallel and Distributed IR. • April 22 Midterm exam. Consultations. Discussion. • April 29 Chapter 11: Multimedia IR: Models and languages • May 6 Paper presentation and discussion. • May 13 Chapter 12: Multimedia IR: Indexing and Searching • May 20 Paper presentation and discussion. • May 27 Thesis presentation. • June 3 Thesis presentation. • June 10 Paper presentation and discussion. • June 17 Final exam. Consultations. Discussion.

  12. Class structure Main course: Information Retrieval • Discussion of previous chapter. Questions • I briefly present a new chapter Research seminar: Natural Language Processing • Discussion of previous paper. Questions. • Identification of possible research topics • Presentation of a new paper or current work • Discussion and questions • Goal: publications!

  13. Evaluation • Oral tests • Written test • Activity in paper presentations and discussions • Preparation of papers for publication

  14. Papers for the next classes • March 11: Challenges in the Interaction of Information Retrieval and Natural Language Processing  Ricardo Baeza-Yates • March 18: Head/Modifier Frames for Information Retrieval Cornelis H.A. Koster

  15. Thank you! Till March 11

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