Paper Info
Title
Opinion-Based Filtering through Trust
Abstract
Recommender systems help users to identify particular items that best match their tastes or preferences. When we apply the agent theory to this domain, a standard centralized recommender system becomes a distributed world of recommender agents. Therefore, due to the agent's world, a new information filtering method appears: the opinion-based filtering method. Its main idea is to consider other agents as personal entities which you can rely on or not. Recommender agents can ask their reliable friends for an opinion about a particular item and filter large sets of items based on it. Reliability is expressed through a trust value with which each agent labels its neighbors. Thus, the opinion-based filtering method needs a model of trust in the collaborative world. The model proposed emphasizes proactiveness since the agent looks for other agents in a situation of lack of information instead of remaining passive or providing either a negative or empty answer to the user. Finally, our social model of trust exploits interactiveness while preserving privacy.
Year
DOI
Venue
2002
10.1007/3-540-45741-0_15
CIA
Keywords
Field
DocType
trust value,collaborative world,opinion-based filtering,recommender system,social model,agent theory,recommender agent,standard centralized recommender system,particular item,empty answer,new information
Recommender system,Data mining,Intelligent agent,World Wide Web,User assistance,Relevance feedback,Computer science,Filter (signal processing),Exploit,Proactivity,User interface
Conference
ISBN
Citations 
PageRank 
3-540-44173-5
40
4.70
References 
Authors
8
3
Name
Order
Citations
PageRank
Miquel Montaner120523.60
Beatriz López211413.76
Josep Lluís De La Rosa326041.38