Paper Info
Title
Opinion-based User Profile Modeling for Contextual Suggestions
Abstract
The problem of contextual suggestion is defined as finding suggested places for a user based on the temporal and geographical context of the user as well as the user's preferences on example places. Existing studies models user preferences based on the descriptive information about the suggestions and might not generalize well. In this paper, we propose to model user profiles based on the opinions about the candidate suggestions. Instead of simply building a profile about "what a user likes or dislikes", we want to build the profile based on "why a user likes or dislikes" so that we can make a more accurate prediction on whether a user would like a new candidate suggestion. In particular, we propose to leverage the opinions from the comments posted by other users to estimate a user's profile. The basic assumption is that the reason why a user likes or dislikes a place is likely to be covered by the reviews posted by other users who share the similar opinions as the user. Experiments results over a TREC collection show that the proposed opinion-based user modeling can indeed outperform the existing description-based methods.
Year
DOI
Venue
2013
10.1145/2499178.2499191
ICTIR
Keywords
Field
DocType
studies models user preference,opinion-based user profile modeling,accurate prediction,existing description-based method,user like,new candidate suggestion,model user profile,contextual suggestions,candidate suggestion,proposed opinion-based user modeling,contextual suggestion,trec collection show,opinion,user modeling
User experience design,World Wide Web,User profile,Computer science,User modeling,Computer user satisfaction,User requirements document,User journey
Conference
Citations 
PageRank 
References 
11
0.92
12
Authors
2
Name
Order
Citations
PageRank
Peilin Yang110012.00
Hui Fang291863.03