A Comparative Study of Boolean Model and Vector Space Model (Vsm) For Information Aggregation from Various Websites Using Web Content Mining Techniques: A Matlab Approach

Abstract: The rapid growth of World Wide Web and the abundance of documents and different forms of information available on it, has recorded the need for good Information Retrieval technique. By and large, three classic framework models have been used in the process of retrieving information: Boolean and Vector Space and Probabilistic. The (standard) Boolean model of information retrieval is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms (a bag-of-words model). Retrieval is based on whether or not the documents contain the query terms and whether they satisfy the boolean conditions described by the query [20]. Gerard Salton is often credited with developing the vector space model (VSM) for information retrieval (IR). The Vector Space Model is an algebraic model used for Information Retrieval. It represents natural language document in a formal manner by the use of vectors in a multi-dimensional space, and allows decisions to be made as to which documents are similar to each other and to the queries fired. vector space models which view documents and queries as vectors in a multidimensional vector space and use distance as a measure of similarity. The vector space model has been studied and used for some time by IR researchers and are quite well understood. Boolean model is a light weight model which matches the query with precise semantics. Because of its Boolean nature, results may be tides, missing partial matching, while on the contrary, vector space model, considering term-frequency, inverse document frequency measures, achieves utmost relevancy in retrieving documents in information retrieval. This proposed model implements and discusses the comparison of information retrieval system between Boolean model and vector space model using MATLAB on non-agricultural universities Website data of Maharashtra State domain

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-10
DOI
https://doi.org/10.5281/zenodo.13637382
Primary Topic
Motor Control and Adaptation
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article
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article

A Comparative Study of Boolean Model and Vector Space Model (Vsm) For Information Aggregation from Various Websites Using Web Content Mining Techniques: A Matlab Approach

Zenodo (CERN European Organization for Nuclear Research)
Motor Control and Adaptation
article

A Comparative Study of Boolean Model and Vector Space Model (Vsm) For Information Aggregation from Various Websites Using Web Content Mining Techniques: A Matlab Approach

article en

Abstract

Abstract: The rapid growth of World Wide Web and the abundance of documents and different forms of information available on it, has recorded the need for good Information Retrieval technique. By and large, three classic framework models have been used in the process of retrieving information: Boolean and Vector Space and Probabilistic. The (standard) Boolean model of information retrieval is a classical information retrieval (IR) model and, at the same time, the first and most-adopted one. The BIR is based on Boolean logic and classical set theory in that both the documents to be searched and the user's query are conceived as sets of terms (a bag-of-words model). Retrieval is based on whether or not the documents contain the query terms and whether they satisfy the boolean conditions described by the query [20]. Gerard Salton is often credited with developing the vector space model (VSM) for information retrieval (IR). The Vector Space Model is an algebraic model used for Information Retrieval. It represents natural language document in a formal manner by the use of vectors in a multi-dimensional space, and allows decisions to be made as to which documents are similar to each other and to the queries fired. vector space models which view documents and queries as vectors in a multidimensional vector space and use distance as a measure of similarity. The vector space model has been studied and used for some time by IR researchers and are quite well understood. Boolean model is a light weight model which matches the query with precise semantics. Because of its Boolean nature, results may be tides, missing partial matching, while on the contrary, vector space model, considering term-frequency, inverse document frequency measures, achieves utmost relevancy in retrieving documents in information retrieval. This proposed model implements and discusses the comparison of information retrieval system between Boolean model and vector space model using MATLAB on non-agricultural universities Website data of Maharashtra State domain

Zenodo (CERN European Organization for Nuclear Research)
Department of Commerce (AU)
Openalex Percentile: Top 60%
Motor Control and Adaptation
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