Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Fab: content-based, collaborative recommendation
Communications of the ACM
GroupLens: applying collaborative filtering to Usenet news
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
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
GRAPE: an expert review assignment component for scientific conference management systems
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Analysis and experimental study of an algorithm for automatic assignment of reviewers to papers
CompSysTech '07 Proceedings of the 2007 international conference on Computer systems and technologies
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Given a large set of items and a set of users, we consider the problem of collecting user preferences - or ratings - on items. The paper describes a simple method which provides an approximate solution to the problem without requiring each user to rate each item. The method relies on an iterative process. Each step, or ballot, requires each user to rate a sample of the items. A collaborative filtering algorithm is then performed to predict the missing ratings as well as their level of confidence (which is initially 0). Perfoming a new ballot allows to improve the accuracy of predictions. The administrator of the system is responsible for stopping the iteration when a satisfactory level is reached.We apply this method to the assignment of reviewers to papers prior to the review phase of conference management, and describe its implementation in the MYREVIEW web-based system.