Paper Info
Title
Context-sensitive automatic categorization of web database query results
Abstract
To deal with the problem of too many answers returned from a Web database in response to a user query, this paper proposes a novel categorization approach which takes advantages of the user contextual preferences to construct a navigational tree in order to reduce the information overload. Based on the user original query, we first speculate how much the user cares about each attribute in the specified context and assign a corresponding weight to it. Then, the categorizing attribute in each level of the tree can be determined according to the weight of the attribute. The categorizing attribute for the first level of the tree is the attribute with the maximum weight. Next, we use the histogram construction algorithm to partition the values of each categories of the tree, the category with the larger exploring probability will be provided earlier to the user. Finally, the navigational tree is generated automatically and presented to the user, such that the user can easily select the relevant tuples matching his needs. Results of a preliminary user study demonstrate that our categorization method can capture the user's preferences effectively.
Year
DOI
Venue
2010
10.1109/FSKD.2010.5569335
FSKD
Keywords
Field
DocType
query results categorization,contextual preferences,web database query,context-sensitive grammars,web database,context sensitive automatic categorization,web sites,information navigation,navigational tree,query processing,probability,databases,information overload,construction industry,histograms,navigation,clustering algorithms
Data mining,Histogram,Categorization,Information overload,Database query,Information retrieval,Tuple,Computer science,User modeling,Cluster analysis,Attribute domain
Conference
Volume
ISBN
Citations 
4
978-1-4244-5931-5
1
PageRank 
References 
Authors
0.35
11
3
Name
Order
Citations
PageRank
Xiangfu Meng15514.18
Jinguang Sun2132.30
Chunxiao Liu310114.77