MohammedAly22/Semantify
A detailed comparison between 3 different techniques (TF-IDF, Doc2Vec, and Sentence Transformers) for performing semantic search on a huge dataset
This project helps you find the most relevant information in a large collection of documents by understanding the meaning and context of your search query, rather than just matching keywords. You input a search query and a dataset of text documents, and it outputs a list of documents most semantically similar to your query. Anyone who needs to quickly pinpoint specific information within vast amounts of text, such as a researcher or content analyst, would find this useful.
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Use this if you need to perform advanced information retrieval on a large text dataset where traditional keyword searches fail to capture the true intent of your query.
Not ideal if your dataset is very small or if simple keyword matching is sufficient for your search needs.
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Feb 19, 2024
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