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Document Similarity in Information Retrieval

Document Similarity in Information Retrieval Mausam (Based on slides of W. Arms, Thomas Hofmann, Ata Kaban, Melanie Martin) Standard Web Search Engine Architecture crawl the web create an inverted index store documents, check for duplicates, extract links inverted index DocIds Slide adapted from Marti Hearst / UC Berkeley] Search engine servers user query show results To user Indexing Subsystem Documents break into tokens stop list* stemming* term weighting* Index database text non-stoplist tokens tokens stemmed terms terms with weights *Indicates optional operation.

(PageRank) 4. Combination methods What happens in major search engines (Googlerank) Vector representation of documents and queries Why do this? • Represents a large space for documents • Compare – Documents – Documents with queries • Retrieve and rank documents with regards to a

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