Topic Extraction from Online Reviews for Classification and Recommendation

Author(s)
Uri
Date Issued
2013-08-09
Date Available
2017-04-28T10:16:50Z
Abstract
Automatically identifying informative reviews is increasingly important given the rapid growth of user generated reviews on sites like Amazon and TripAdvisor. In this paper, we describe and evaluate techniques for identifying and recommending helpful product reviews using a combination of review features, including topical and sentiment information, mined from a review corpus.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
AAAI
Start Page
1310
End Page
1316
Copyright (Published Version)
2013 AAAI
Subjects

Recommender systems

Classification

Reviews

Web versions
Language
English
Status of Item
Peer reviewed
Journal
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13)
Conference Details
Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI 13), Beijing, China, 3-9 August 2013
ISBN
9781577356332
This item is made available under a Creative Commons License
File(s)
Loading...
Thumbnail Image
Name

Topic Extraction from Online Reviews for Classification and Recommendation.pdf

Size

696.73 KB

Format

Adobe PDF

Checksum (MD5)

c81569dbcfd0242cb482504c7a011f18

Owning collection
Insight Research Collection
Mapped collections
CLARITY Research Collection•
Computer Science Research Collection