Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Effects of adjective orientation and gradability on sentence subjectivity
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
On the temporal dimension of search
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Adding the Temporal Dimension to Search " A Case Study in Publication Search
WI '05 Proceedings of the 2005 IEEE/WIC/ACM International Conference on Web Intelligence
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Opinion Searching in Multi-Product Reviews
CIT '06 Proceedings of the Sixth IEEE International Conference on Computer and Information Technology
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Informed Recommender: Basing Recommendations on Consumer Product Reviews
IEEE Intelligent Systems
Designing novel review ranking systems: predicting the usefulness and impact of reviews
Proceedings of the ninth international conference on Electronic commerce
Mining opinion features in customer reviews
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Opinion sentence search engine on open-domain blog
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Feature-Based Visual Sentiment Analysis of Text Document Streams
ACM Transactions on Intelligent Systems and Technology (TIST)
Transafe: a crowdsourced mobile platform for crime and safety perception management
ACM SIGCAS Computers and Society - Special Issue on Selected Papers from ISTAS 2011
Senti-lexicon and improved Naïve Bayes algorithms for sentiment analysis of restaurant reviews
Expert Systems with Applications: An International Journal
Survey on mining subjective data on the web
Data Mining and Knowledge Discovery
International Journal of Intelligent Systems
Identifying helpful online reviews: A product designer's perspective
Computer-Aided Design
Summarising customer online reviews using a new text mining approach
International Journal of Business Information Systems
A multidimensional data model using the fuzzy model based on the semantic translation
Information Systems Frontiers
Visualizing sentiment: do you see what i mean?
Proceedings of the companion publication of the 19th international conference on Intelligent User Interfaces
| Hi-index | 12.05 |
With the rapid growth of e-commerce, there are a great number of customer reviews on the e-commerce websites. Generally, potential customers usually wade through a lot of on-line reviews in order to make an informed decision. However, retrieving sentiment information relevant to customer's interest still remains challenging. Developing a sentiment mining and retrieval system is a good way to overcome the problem of overloaded information in customer reviews. In this paper, we propose a sentiment mining and retrieval system which mines useful knowledge from consumer product reviews by utilizing data mining and information retrieval technology. A novel ranking mechanism taking temporal opinion quality (TOQ) and relevance into account is developed to meet customers' information need. Besides the trend movement of customer reviews and the comparison between positive and negative evaluation are presented visually in the system. Experimental results on a real-world data set show the system is feasible and effective.