Title
VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data.
Abstract
In this article, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents, VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Additionally, we present preliminary user study results for evaluating the effectiveness of the system.
Year
DOI
Venue
2018
10.1145/3070616
TKDD
Keywords
Field
DocType
Recommendation, clustering, dimension reduction, information retrieval, topic modeling
Recommender system,Dimensionality reduction,Information retrieval,Computer science,Visual analytics,Topic model,Cluster analysis,Dynamic query
Journal
Volume
Issue
ISSN
12
1
1556-4681
Citations 
PageRank 
References 
1
0.35
25
Authors
11
Name
Order
Citations
PageRank
Jaegul Choo155646.81
Hannah Kim21036.77
Edward Clarkson3887.53
Zhicheng Liu493752.56
Changhyun Lee510.35
Fuxin Li677252.53
Hanseung Lee720.70
Ramakrishnan Kannan813318.57
Charles D. Stolper91396.39
John Stasko105655494.01
Haesun Park113546232.42