Authors:
Yu Fujimoto
1
;
Hideitsu Hino
2
and
Noboru Murata
2
Affiliations:
1
Aoyama Gakuin University, Japan
;
2
Waseda Univ., Japan
Keyword(s):
Bradley-Terry model, Mixture model, EM algorithm, Preference map, Data visualization.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Pre-Processing and Post-Processing for Data Mining
;
Symbolic Systems
;
Visual Data Mining and Data Visualization
Abstract:
In this paper, we propose a visualization technique of a statistical relation of users and preference of items based on a mixture model. In our visualization, items are given as points in a few dimensional preference space, and user specific preferences are given as lines in the same space. The relationship between items and user preferences are intuitively interpreted via projections from points onto lines. As a primitive implementation, we introduce a mixture of the Bradley-Terry models, and visualize the relation between items and user preferences with benchmark data sets.