Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
A personalized recommender system for travel information
UbiMob '04 Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing
Recommender System Based on Consumer Product Reviews
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
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
Exploring Movie Recommendation System Using Cultural Metadata
Transactions on Edutainment II
Using twitter to recommend real-time topical news
Proceedings of the third ACM conference on Recommender systems
Personalized and automatic social summarization of events in video
Proceedings of the 16th international conference on Intelligent user interfaces
On using the real-time web for news recommendation & discovery
Proceedings of the 20th international conference companion on World wide web
Terms of a feather: content-based news recommendation and discovery using twitter
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Personalized activity streams: sifting through the "river of news"
Proceedings of the fifth ACM conference on Recommender systems
From chatter to headlines: harnessing the real-time web for personalized news recommendation
Proceedings of the fifth ACM international conference on Web search and data mining
Sentimental product recommendation
Proceedings of the 7th ACM conference on Recommender systems
Journal of Information Science
Followee recommendation based on text analysis of micro-blogging activity
Information Systems
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The so-called real-time web (RTW) is a web of opinions, comments, and personal viewpoints, often expressed in the form of short, 140-character text messages providing abbreviated and personalized commentary in real-time. Twitter is undoubtedly the king of the RTW. It boasts 100+ million users and generates in the region of 50m tweets per day. This RTW data is far from the structured data (ratings, product features, etc.) familiar to recommender systems research, but it is useful to consider its applicability to recommendation scenarios. In this short paper we describe an experiment to look at harnessing the real-time opinions of movie fans, expressed through the Twitter-like short textual reviews available on the Blippr service (www.blippr.com). In particular we describe how users and movies can be represented from the terms used in their associated reviews and describe a number of experiments to highlight the recommendation potential of this RTW data-source and approach.