Bibliographic Citation Recommender System

Please use this identifier to cite or link to this item: http://hdl.handle.net/10263/7306

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DC Field	Value	Language
dc.contributor.author	Ashrit, P Omkar	-
dc.date.accessioned	2022-03-24T05:35:02Z	-
dc.date.available	2022-03-24T05:35:02Z	-
dc.date.issued	2021-07	-
dc.identifier.citation	19p.	en_US
dc.identifier.uri	http://hdl.handle.net/10263/7306	-
dc.description	Dissertation under the supervision of Mandar Mitra	en_US
dc.description.abstract	With increasing volume of published scholarly articles every year, it becomes demanding to include appropriate references in a paper. Recommendation systems for bibliographic citations suggests possible references to authors. We discuss performances of di↵erent recommendation approaches in this report. We also have implemented a prototype extension for VS Code which suggests references in real time to the authors. This is the link of the GitHub repository for the dissertaion.	en_US
dc.language.iso	en	en_US
dc.publisher	Indian Statistical Institute, Kolkata.	en_US
dc.relation.ispartofseries	Dissertation;CS1914	-
dc.subject	Bibliographic Citation	en_US
dc.subject	Recommendation System	en_US
dc.subject	Collaborative Filtering	en_US
dc.subject	Content Based Methods	en_US
dc.title	Bibliographic Citation Recommender System	en_US
dc.type	Other	en_US
Appears in Collections:	Dissertations - M Tech (CS)

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