Sentimental Product Recommendation

Author(s)
Uri
Date Issued
2013-10-16
Date Available
2017-04-28T10:01:23Z
Abstract
This paper describes a novel approach to product recommendation that is based on opinionated product descriptions that are automatically mined from user-generated product reviews. We present a recommendation ranking strategy that combines similarity and sentiment to suggest products that are similar but superior to a query product according to the opinion of reviewers. We demonstrate the benefits of this approach across a variety of Amazon product domains.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Start Page
411
End Page
414
Copyright (Published Version)
2013 ACM
Subjects

Recommender systems

User-generated review...

Opinion mining

Sentiment-based produ...

DOI
Language
English
Status of Item
Peer reviewed
Journal
Proceedings of RecSys '13: 7th ACM conference on Recommender systems
Conference Details
RecSys '13: 7th ACM conference on Recommender systems, Hong Kong, China, 12-16 October 2013
This item is made available under a Creative Commons License
File(s)
Loading...
Thumbnail Image
Name

Sentimental Product Recommendation.pdf

Size

685.04 KB

Format

Adobe PDF

Checksum (MD5)

a31eda4f8d256b4f7ef7283d7dc75d1c

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