information retrieval through keyword search - Search
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  1. Unite.AI
    https://www.unite.ai/from-keyword-search-to-openais-deep-research-how-ai-is-redefini…
    From Keyword Search to OpenAI's Deep Research: How AI is Redefining ...
    What is a keyword search algorithm?
    Keyword searching algorithms are fundamental to search engines, enabling them to retrieve relevant documents or web pages based on user-inputted keywords. Keyword searching is a fundamental aspect of search engines, and several algorithms contribute to efficiently retrieving relevant results based on user-entered keywords.
    geeksforgeeks.org
    Mastering Information Retrieval: Building Intelligent S…

    1.1 Recap and Objectives for this Article In the first part of the “Mastering Information Retrieval” series, we explored the foundation of information retrieval through keyword search. We discussed different types of keyword search, their implementation, and evaluation. In this article, we will delve into more advanced information retrieval techniq...

    Medium

    2.1 Definition and Concept of Tf-IDF Term Frequency-Inverse Document Frequency (TF-IDF) is a widely used technique in information retrieval that helps to quantify the importance of terms within a document and across a collection of documents. The main idea behind TF-IDF is that terms that appear frequently in a document but rarely across the entire...

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    3.1. Definition and concept of Vector Space Model The Vector Space Model (VSM) is an algebraic model used in information retrieval to represent documents and queries as vectors in a high-dimensional space. Each dimension in this space corresponds to a unique term from the document collection, and the value of a vector in that dimension represents t...

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    4.1. Data preparation and preprocessing We will be using the same preprocessed data from the last article where we added a new column to our DataFrame to be used by our model. Here is the code: 4.2. Implementing TF-IDF and Vector Space Model 1. Create the TF-IDF matrix: We first create the term-document matrix using the TF-IDF weighting scheme. To ...

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    5.1. Advantages and disadvantages of TF-IDF and Vector Space Model compared to keyword search Advantages: 1. TF-IDF and Vector Space Model capture the semantic importance of terms in documents, which can lead to more relevant search results. 2. By considering term weights, the Vector Space Model provides a more nuanced representation of document co...

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