Oh, the joys of latent semantic indexing! Latent semantic indexing is the crux of every Google search that a user performs. So, understanding latent semantic indexing brings an admiration for the intellect that created the process. The story of latent semantic indexing is a fascinating one.
To understand latent semantic indexing, we actually need to do a semantic analysis of the term itself. That means we need to break the term into its component words and see how the meaning of each word contributes to the meaning of latent semantic indexing as a whole. So, we've already told you that "semantic" refers to the meaning of words. In the context of a Google search, this means the meaning of every word that is in every document on the internet. That, of course, is a lot of words, but that is why a search engine is constantly browsing the internet, indexing all the words in all the documents.
"Indexing" means compling a list of things, in this case words, in a defined order. In other words, lining up all the words in terms of what they mean. Part of the trick here is that words can have more than one meaning, and this is where the word "latent" comes in to latent semantic indexing. One meaning may be obvious, but another meaning may be latent or hidden. And the meaning may depend on the context of the word. For example, "lab" may refer to a laboratory if the document is scientific, but it may refer to a Retriever if the document is about dogs. So a search engine needs to keep track of all the meanings of every word in order to come up with the latent semantic indexing of the document and an overall meaning. In this context, the term "overall meaning" refers to a score that a document is assigned for some standard search phrases.
Users tend to use the same search phrases over and over in order to look for information. To extend our example, the words "lab equipment" are a steady search term. The word "equipment" is not generally used with dogs, so documents that have the word "lab" but no other scientific terms will not be put as high on the list of valid documents for this search term. Those documents will be considered to be more likely about dogs or some other type of lab, and thus they will not be returned to the user in a query for "lab equipment".
So latent semantic indexing plays an important role in every search that Google or any other search engine makes on the internet. We normally do not see LSI at work, but now that you've read this article, you'll know that it is chugging along in the background every time you do an internet query. Of course, there is more to a search than just latent semantic indexing, but it is an important step of every search. The Joys of Latent Semantic Indexing
To understand latent semantic indexing, we actually need to do a semantic analysis of the term itself. That means we need to break the term into its component words and see how the meaning of each word contributes to the meaning of latent semantic indexing as a whole. So, we've already told you that "semantic" refers to the meaning of words. In the context of a Google search, this means the meaning of every word that is in every document on the internet. That, of course, is a lot of words, but that is why a search engine is constantly browsing the internet, indexing all the words in all the documents.
"Indexing" means compling a list of things, in this case words, in a defined order. In other words, lining up all the words in terms of what they mean. Part of the trick here is that words can have more than one meaning, and this is where the word "latent" comes in to latent semantic indexing. One meaning may be obvious, but another meaning may be latent or hidden. And the meaning may depend on the context of the word. For example, "lab" may refer to a laboratory if the document is scientific, but it may refer to a Retriever if the document is about dogs. So a search engine needs to keep track of all the meanings of every word in order to come up with the latent semantic indexing of the document and an overall meaning. In this context, the term "overall meaning" refers to a score that a document is assigned for some standard search phrases.
Users tend to use the same search phrases over and over in order to look for information. To extend our example, the words "lab equipment" are a steady search term. The word "equipment" is not generally used with dogs, so documents that have the word "lab" but no other scientific terms will not be put as high on the list of valid documents for this search term. Those documents will be considered to be more likely about dogs or some other type of lab, and thus they will not be returned to the user in a query for "lab equipment".
So latent semantic indexing plays an important role in every search that Google or any other search engine makes on the internet. We normally do not see LSI at work, but now that you've read this article, you'll know that it is chugging along in the background every time you do an internet query. Of course, there is more to a search than just latent semantic indexing, but it is an important step of every search. The Joys of Latent Semantic Indexing
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Users tend to use the same search phrases over and over in order to look for information. To extend our example, the words "lab equipment" are a steady search term. The word.... Learn more at Latent Semantic Indexing and Latent Semantic Indexing
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