lecture03 - Information Retrieval Ranking Fernando Diaz...

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Information Retrieval: Ranking Fernando Diaz Yahoo! Labs February 7, 2011 1 / 64
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Outline Introduction to Information Retrieval Vector Space Model PageRank Ranking in Practice 2 / 64
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Introduction to Information Retrieval 3 / 64
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Information Retrieval given a query and a corpus , find relevant documents . 4 / 64
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Information Retrieval given a query and a corpus , find relevant documents . query : user’s expression of the information need 4 / 64
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Information Retrieval given a query and a corpus , find relevant documents . query : user’s expression of the information need corpus : the repository of retrievable items 4 / 64
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Information Retrieval given a query and a corpus , find relevant documents . query : user’s expression of the information need corpus : the repository of retrievable items relevance : satisfaction of the information need 4 / 64
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Examples of Information Retrieval Problems Web Search given a keyword and a web crawl , find relevant URLs . 5 / 64
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Examples of Information Retrieval Problems Image Search given a keyword and image database , find relevant images . 6 / 64
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Examples of Information Retrieval Problems Question Answering given a question and available text, rules, logic , find an answer . 7 / 64
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Examples of Information Retrieval Problems Job Search given a resume and job advertisements , find relevant jobs . 8 / 64
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Examples of Information Retrieval Problems Applicant Search given a advertisement and resumes , find good candidates . 9 / 64
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History 1950s : early information work in problem definition, metrics. 1960s : Gerard Salton begins work on SMART; Cranfield evaluation method defined. 1970s : information retrieval research community developed (SIGIR); many fundamental concepts proposed (e.g. cluster-based retrieval, pseudo-relevance feedback). 1980s : development of first commercial information retrieval systems. 1990s : TREC conferences begin, standardizing evaluation; web search engines developed, using many fundamental IR techniques. 10 / 64
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Text REtrieval Conference (TREC) Started in 1992 as a forum to compare IR systems using standard test collections, ensuring reproducibility . Initially focused on ad hoc retrieval (keyword search), the scope has broadened to include multi-lingual retrieval, legal retrieval, and question answering. Allowed for accelerated comparison and testing of algorithmic changes across systems. Resulted in similar forums in Europe (CLEF), Asia (NTCIR), and India (FIRE). 11 / 64
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IR ̸ = DB DB IR data structured semi-structured fields clear semantics free text queries structured free text matching exact imprecise ranking none important based on a table by James Allan 12 / 64
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Fundamental Problems in Information Retrieval Research Effectiveness : how well does the system satisfy the user’s information need? algorithms interaction evaluation Efficiency : how efficiently does the system satisfy the user’s information need?
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