GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fab: content-based, collaborative recommendation
Communications of the ACM
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A personalized recommender system for travel information
UbiMob '04 Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing
IEEE Transactions on Knowledge and Data Engineering
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Utility scoring of product reviews
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Recommender System Based on Consumer Product Reviews
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
A new approach to evaluating novel recommendations
Proceedings of the 2008 ACM conference on Recommender systems
Micro-blogging as online word of mouth branding
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Tagommenders: connecting users to items through tags
Proceedings of the 18th international conference on World wide web
A survey on sentiment detection of reviews
Expert Systems with Applications: An International Journal
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Using emoticons to reduce dependency in machine learning techniques for sentiment classification
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Statistical Modeling of Diversity in Top-N Recommender Systems
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Content-based recommendation systems
The adaptive web
Content-based recommendation in social tagging systems
Proceedings of the fourth ACM conference on Recommender systems
Towards text-based recommendations
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Creating subjective and objective sentence classifiers from unannotated texts
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Preventing automatic user profiling in Web 2.0 applications
Knowledge-Based Systems
Dynamic adaptation of numerical attributes in a user profile
Applied Intelligence
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Real-time web (RTW) services such as Twitter allow users to express their opinions and interests, often expressed in the form of short text messages providing abbreviated and highly personalized commentary in real-time. Although this RTW data is far from the structured data (movie ratings, product features, etc.) that is familiar to recommender systems research, it can contain useful consumer reviews on products, services and brands. This paper describes how Twitter-like short-form messages can be leveraged as a source of indexing and retrieval information for product recommendation. In particular, we describe how users and products can be represented from the terms used in their associated reviews. An evaluation performed on four different product datasets from the Blippr service shows the potential of this type of recommendation knowledge, and the experiments show that our proposed approach outperforms a more traditional collaborative-filtering based approach.