Paper Info
Title
TreeQueST: A Treemap-Based Query Sandbox for Microdocument Retrieval
Abstract
Scatter/Gather-browsing has been proposed as a technique for information retrieval that fosters understanding of textual data and identification of key documents by means of exploration and drill-down. It has been found that such approaches are more expensive but not more effective than less interactive search solutions for traditional retrieval tasks. In this paper, however, we show that the rise of online micro document platforms, such as Twitter, has brought new relevance to the technique for finding and understanding information about recent events. Our novel approach builds on hierarchical topic clustering combined with a tree map-based visualization to provide a highly interactive information management and query sandboxing space. Large volumes of data, only accessible through rate- and throughput-limited channels, can thus effectively be filtered and retrieved using iteratively optimized queries. We conducted a user study that demonstrates the performance of our approach compared to plain text search based on the Twitter engine.
Year
DOI
Venue
2015
10.1109/HICSS.2015.206
System Sciences
Keywords
Field
DocType
data visualisation,document handling,pattern clustering,query processing,search engines,social networking (online),trees (mathematics),treequest,twitter engine,hierarchical topic clustering,information retrieval,microdocument retrieval,tree map-based visualization,treemap-based query sandbox,hierarchical topics,twitter,visual analytics,media,visualization,data visualization,navigation
Data mining,Web search query,Data visualization,Query language,Query expansion,Information retrieval,Information visualization,Computer science,Web query classification,Visual analytics,Cluster analysis
Conference
ISSN
Citations 
PageRank 
1530-1605
1
0.35
References 
Authors
19
2
Name
Order
Citations
PageRank
Dennis Thom117810.72
Thomas Ertl24417401.52