Information Retrieval System Using BM25, Pivoted Normalization and CombSUM Method

dc.contributor.author	Khaing, Nu Yin
dc.contributor.author	Htwe, Ah Nge
dc.date.accessioned	2021-06-11T05:57:12Z
dc.date.available	2021-06-11T05:57:12Z
dc.date.issued	2021-01
dc.identifier.uri	https://onlineresource.ucsy.edu.mm/handle/123456789/2587
dc.description.abstract	Retrieving information is difficult and time consuming for searching a variety and large number of documents on the digital library. This paper intends to implement effective keyword search system for digital library.BM25 and Pivoted Normalization are best retrieval models for information retrieval system. The CombSUM is combining these two methods to get more relevant documents and to give better output result. The proposed system will help the user to get all relevant documents according to the given query. When the user enters the query, the most relevant documents are ranked by using BM25, Pivoted Normalization Method and CombSUM.	en_US
dc.language.iso	en	en_US
dc.publisher	University of Computer Studies, Yangon	en_US
dc.subject	BM25	en_US
dc.subject	CombSUM	en_US
dc.subject	Pivoted Normalization Method	en_US
dc.title	Information Retrieval System Using BM25, Pivoted Normalization and CombSUM Method	en_US
dc.type	Thesis	en_US