9-IR-VSM

9-IR-VSM - Information Retrieval and Vector Space Model...

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Information Retrieval and ector Space Model Vector Space Model CS273 - Data and Knowledge Bases Xifeng Yan Computer Science niversity of California at Santa Barbara University of California at Santa Barbara
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Department of Computer Science Thursday, October 20, 2011 (No Class) But you are required to attend the talk given by Dr. Hanghang Tong from IBM T. J. Watson Research Center itle: Fast Algorithms for Mining Large Graphs Title: Fast Algorithms for Mining Large Graphs 3:30 – 4:30 PM Computer Science Conference Room, Harold Frank Hall m 132 Rm. 1132 CS273: Data and Knowledge Bases | University of California at Santa Barbara 2
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Department of Computer Science Readings: 1. A Vector Space Model for Automatic Indexing, G. Salton, A. Wong, C. S. Yang 2. Modern Information Retrieval: A Brief Overview: Amit Singhal 3. Term-Weighting Approaches in Automatic Text Retrieval, Gerard Salton and Christopher Buckley. 4. Pivoted Document Length Normalization. Amit Singhal, Chris Buckley, Mandar Mitra. CS273: Data and Knowledge Bases | University of California at Santa Barbara 3
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Department of Computer Science Problem Formulation: Informal User has an information need Short-term (“ad hoc”), e.g., “digital camera, iphone review” Long-term, e.g., “new data mining algorithm” There exists an information source (Relatively) static, e.g., library system (Inherently) dynamic, e.g., news articles oal is to find information items that can satisfy a user’s Goal is to find information items that can satisfy a user s information need CS273: Data and Knowledge Bases | University of California at Santa Barbara 4 slides by courtesy of Zhai with modifications
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Department of Computer Science Ad hoc Retrieval vs. Information Filtering Ad hoc retrieval Short-term information need + static source User “pulls” information, e.g., web search Information filtering(routing) Long-term information need + dynamic source System “pushes” information to user, e.g., news filter CS273: Data and Knowledge Bases | University of California at Santa Barbara 5
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Department of Computer Science Importance of Ad hoc Retrieval Directly manages any existing large collection of information There are many many “ad hoc” information needs. A long-term information need can be satisfied through equent ad hoc retrieval frequent ad hoc retrieval Basic techniques of ad hoc retrieval can be used for filtering and other “non-retrieval” tasks, such as automatic ummarization summarization. CS273: Data and Knowledge Bases | University of California at Santa Barbara 6
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Department of Computer Science The Ad hoc Retrieval Problem Query: Description of information need, e.g., Boolean: “laptop” AND (“cheap” OR “sale”) English: “cheap laptop on sale” Document: Information item, e.g., ,g , Textual (possibly with structural information) Multi-media Database/Collection/Corpus: a set of docs Retrieval task: find docs relevant to a query in one or more collections CS273: Data and Knowledge Bases | University of California at Santa Barbara 7
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This note was uploaded on 01/09/2012 for the course CS CS273 taught by Professor Xifengyan during the Spring '11 term at UCSB.

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9-IR-VSM - Information Retrieval and Vector Space Model...

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