Document indexing, searching, and ranking with semantic intelligence
Abstract:
There is a need for solutions that perform preprocessing and/or searching of documents with semantic intelligence. This need can be addressed by, for example, by performing pre-processing of each document of a plurality of documents to generate an indexed representation for the document by identifying sentences in the document; determining, for each n-gram of one or more n-grams associated with the document, one or more n-gram semantic scores based semantic proximity indicators for the n-gram; determining, based at least in part on each one or more n-gram semantic scores, one or more sentence semantic labels for each sentence in the document; and determining the indexed representation for the document based at least in part on the one or more sentence semantic labels for the document; performing the search query based each indexed representation associated with a document; and transmitting the result to a computing device associated with the search query.
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