What are polysemy?
Posted: Sun Feb 09, 2025 8:08 am
Polysemy is a linguistic term for a word that has more than one meaning. However, polysemy has different associated meanings. Take the word "drive" for example: you can drive a car, or you can drive your friends home from the bar, or you can simply drive for a long time. At the same time the word can mean a determination, a journey, a broad pass for a vehicle, a computer part, etc.
What are homophones?
A slightly different phenomenon is homonymy, when words are spelled the same homographs or pronounced the same homophones, but mean different concepts, regardless of origin.
Synonyms and polysemy are the main reasons why exact georgia mobile database keyword matching doesn’t work for search engines.
LSI reveals latent semantic structures that may be hidden or obscured due to variability in wording. This technique allows finding similarities between multiple documents in a text collection and retrieving the documents that are most relevant to the searcher's query.
Mathematical Description of LSI
LSI uses the term-document matrix and singular value decomposition SVD, a common linear algebra technique, to learn concept relevance in a body of text.
LSI first constructs a term-document matrix to identify the occurrences of unique terms in a collection of documents. Rows correspond to terms, columns correspond to documents, and cells indicate the number of times a word appears in a document.
What are homophones?
A slightly different phenomenon is homonymy, when words are spelled the same homographs or pronounced the same homophones, but mean different concepts, regardless of origin.
Synonyms and polysemy are the main reasons why exact georgia mobile database keyword matching doesn’t work for search engines.
LSI reveals latent semantic structures that may be hidden or obscured due to variability in wording. This technique allows finding similarities between multiple documents in a text collection and retrieving the documents that are most relevant to the searcher's query.
Mathematical Description of LSI
LSI uses the term-document matrix and singular value decomposition SVD, a common linear algebra technique, to learn concept relevance in a body of text.
LSI first constructs a term-document matrix to identify the occurrences of unique terms in a collection of documents. Rows correspond to terms, columns correspond to documents, and cells indicate the number of times a word appears in a document.