Name
Abstract | ||
|---|---|---|
The use of association patterns for text categorization has attracted great interest and a variety of useful methods have been developed. However, the key characteristics of pattern-based text categorization remain unclear. Indeed, there are still no concrete answers for the following two questions: First, what kind of association patterns are the best candidate for pattern-based text categorization? Second, what is the most desirable way to use patterns for text categorization? In this paper, we focus on answering the above two questions. Specifically, we show that hyperclique patterns are more desirable than frequent patterns for text categorization. Along this line, we develop an algorithm for text categorization using hyperclique patterns. The experimental results show that our method provides better performance than state-of-the-art methods in terms of both computational performance and classification accuracy. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1145/1183614.1183728 | CIKM |
Keywords | Field | DocType |
association pattern,pattern-based text,best candidate,classification accuracy,computational performance,concrete answer,hyperclique pattern,adapting association pattern,text categorization,better performance,pattern-based text categorization,data mining | Data mining,Text mining,Information retrieval,Computer science,Text categorization | Conference |
ISBN | Citations | PageRank |
1-59593-433-2 | 0 | 0.34 |
References | Authors | |
10 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tieyun Qian | 1 | 177 | 28.81 |
| Hui Xiong | 2 | 4958 | 290.62 |
| Yuanzhen Wang | 3 | 86 | 11.78 |
| Enhong Chen | 4 | 2106 | 165.57 |