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  1. #16
    Registered User
    Join Date
    Aug 2018
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    679
    LSI is a process found in Natural Language Processing (NLP). NLP is a subset of linguistics and information engineering, with a focus on how machines interpret human language. A key part of this study is distributional semantics. This model helps us understand and classify words with similar contextual meanings within large data sets.

    Developed in the 1980s, LSI uses a mathematical method that makes information retrieval more accurate. This method works by identifying the hidden contextual relationships between words. It may help you to break it down like this:

    Latent → Hidden
    Semantic → Relationships Between Words
    Indexing → Information Retrieval
    Last edited by discusshostingadmin; 08-21-2020 at 06:52 AM.

  2. #17
    Senior Member
    Join Date
    Dec 2019
    Posts
    1,473
    Latent semantic analysis is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.

  3. #18
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    Join Date
    Dec 2020
    Location
    Bangalore
    Posts
    76
    Latent Semantic Indexing, also known as latent semantic analysis, is a mathematical practice that helps classify and retrieve information on particular key terms and concepts using singular value decomposition (SVD).




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  4. #19

  5. #20
    Senior Member
    Join Date
    Mar 2020
    Posts
    1,139
    Latent semantic analysis is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.

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