Database Reference
In-Depth Information
Chapter 1
Automatic Categorization of
Web Database Query Results
Xiangfu Meng
Liaoning Technical University, China
Li Yan
Northeastern University, China
Z. M. Ma
Northeastern University, China
ABSTRACT
Web database queries are often exploratory. The users often find that their queries return too many
answers and many of them may be irrelevant. Based on different kinds of user preferences, this chapter
proposes a novel categorization approach which consists of two steps. The first step analyzes query his-
tory of all users in the system offline and generates a set of clusters over the tuples, where each cluster
represents one type of user preference. When a user issues a query, the second step presents to the user
a category tree over the clusters generated in the first step such that the user can easily select the subset
of query results matching his needs. The problem of constructing a category tree is a cost optimization
problem and heuristic algorithms were developed to compute the min-cost categorization. The efficiency
and effectiveness of our approach are demonstrated by experimental results.
INTRODUCTION
As internet becomes ubiquitous, many people are searching their favorite cars, houses, stocks, etc. over
the Web databases. However, Web database queries are often exploratory. The users often find that
their queries return too many answers, which are commonly referred to as “information overload”. For
