{"id":274635,"date":"2007-02-01T00:00:06","date_gmt":"2007-02-01T08:00:06","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=274635"},"modified":"2018-10-16T21:03:19","modified_gmt":"2018-10-17T04:03:19","slug":"lsa-and-information-retrieval-getting-back-to-basics","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/lsa-and-information-retrieval-getting-back-to-basics\/","title":{"rendered":"LSA and information retrieval: Getting back to basics"},"content":{"rendered":"

Latent semantic analysis (LSA) was first introduced in Dumais, Furnas, Landauer, Deerwester, and Harshman (1988) (opens in new tab)<\/span><\/a> and Deerwester, Dumais, Furnas, Landauer, and Harshman (1990) (opens in new tab)<\/span><\/a> as a technique for improving information retrieval. Most web, enterprise, and desktop search engines work by matching words in a user \u2018s query with words in documents. Information retrieval systems that depend on lexical matching suffer from two problems. First, because the same literal word can have many different meanings, irrelevant information is retrieved when searching. Second, because there are different ways to describe the same object or concept, relevant information can be missed. LSA was designed to address these fundamental retrieval problems. The key idea in LSA was to use dimension reduction techniques to map documents and terms into a lower dimensional semantic space.<\/p>\n","protected":false},"excerpt":{"rendered":"

Latent semantic analysis (LSA) was first introduced in Dumais, Furnas, Landauer, Deerwester, and Harshman (1988) and Deerwester, Dumais, Furnas, Landauer, and Harshman (1990) as a technique for improving information retrieval. Most web, enterprise, and desktop search engines work by matching words in a user \u2018s query with words in documents. Information retrieval systems that depend […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13555],"msr-publication-type":[193719],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-274635","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-search-information-retrieval","msr-locale-en_us"],"msr_publishername":"","msr_edition":"LSA: A Road to 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