Myanmar News Retrieval in Vector Space Model using Cosine Similarity Measure

Myanmar News Retrieval in Vector Space Model using Cosine Similarity Measure

Information Retrieval (IR) is an effective means of retrieving the best relevant document to user query. Nowadays, the problem of documents similarity deals with IR is retrieving required information from a large amount of data. In this paper we studied a Vector Space Model (VSM) that is used in IR...

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Bibliographic Details
Published in:2020 IEEE Conference on Computer Applications(ICCA) pp. 1 - 5
Main Authors: Oo, Hay Man, Pa, Win Pa
Format: Conference Proceeding
Language:English
Published: IEEE 01-02-2020
Subjects:
Computational modeling
Data models
Extraterrestrial measurements
Indexes
Natural language processing
Web search
Online Access:Get full text
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Summary:Information Retrieval (IR) is an effective means of retrieving the best relevant document to user query. Nowadays, the problem of documents similarity deals with IR is retrieving required information from a large amount of data. In this paper we studied a Vector Space Model (VSM) that is used in IR and represents a document as a vector in an n-dimensional space, where each dimensional represents a term and measured through cosine angle between two vectors. The objective of this paper is to retrieve the relevant file from Myanmar news data sets using cosine similarity measure in VSM to user's query. Evaluations are done in terms of similarity score by Precision, Recall and F-score.
DOI:10.1109/ICCA49400.2020.9022845