Personalized Review Selection
Version 2 2024-06-06, 03:02
Version 1 2019-01-01, 00:00
conference contribution
posted on 2024-06-06, 03:02 authored by Y Lei, Ziwei HouZiwei Hou, H Xia, J Tan, X Li, M Al-Khiza'Ay, Gang LiGang Li© 2019 Procedia Computer Science. All rights reserved. With the popularity of the online social network, reviews gradually becoming the main data source for users to understand the qualities of the goods to be purchased. However, with the proliferate of online reviews, these large amounts of reviews make it difficult for users to select useful information. Aiming to enable users to quickly obtain valid information from large amounts of reviews, this paper proposes a new method named PG to implicate personalized review selection. The proposed method in our paper is efficient for users by helping them select useful information from massive reviews.
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Chennai, IndiaOpen access
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E1 Full written paper - refereedEditor/Contributor(s)
Nithyanandam P, Parvathi R, Jagadeesh Kannan R, Nayeemulla Khan AVolume
165Pagination
158-165Start date
2019-11-11End date
2019-11-12eISSN
1877-0509Title of proceedings
ICRTAC - DISRUP - TIV INNOVATION 2019 : Proceedings of the 2nd Trends in Advanced Computing 2019 International ConferenceEvent
Recent Trends in Advanced Computing. Conference (2nd. (2019 : Chennai, India)Publisher
ElsevierPlace of publication
Amsterdam, The NetherlandsSeries
Procedia Computer ScienceUsage metrics
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