What is Latent Semantic Indexing?
Latent Semantic Indexing (LSI) is an indexing and database retrieval method that uses Singular Value Decomposition (SVD) and Correspondence Analysis to identify patterns in the relationships between terms and concepts contained in an unstructured collection of text. Latent Semantic Indexing then extracts that concept by establishing associations between those terms that occur in similar contexts.
Latent Semantic Indexing has ability to correlate semantically related terms that are latent in a collection of text. The method, also called Latent Semantic Analysis (LSA), uncovers the underlying latent semantic structure in the usage of words in a body of text and how it can be used to extract the meaning of the text in response to user queries, commonly referred to as concept searches. Queries, or concept searches, against a set of documents that have undergone Latent Semantic Indexing (LSI) will return results that are conceptually similar in meaning to the search criteria even if the results don’t share a specific word or words with the search criteria.
Latent Semantic Indexing (LSI) is an indexing and database retrieval method that uses Singular Value Decomposition (SVD) and Correspondence Analysis to identify patterns in the relationships between terms and concepts contained in an unstructured collection of text. Latent Semantic Indexing then extracts that concept by establishing associations between those terms that occur in similar contexts.
Latent Semantic Indexing has ability to correlate semantically related terms that are latent in a collection of text. The method, also called Latent Semantic Analysis (LSA), uncovers the underlying latent semantic structure in the usage of words in a body of text and how it can be used to extract the meaning of the text in response to user queries, commonly referred to as concept searches. Queries, or concept searches, against a set of documents that have undergone Latent Semantic Indexing (LSI) will return results that are conceptually similar in meaning to the search criteria even if the results don’t share a specific word or words with the search criteria.
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