Name
Abstract | ||
|---|---|---|
As the amount of available information on the Internet grows, it is becoming increasingly difficult for users to find information that is relevant to their needs. Against this backdrop, a need for an automated tool that can find information quickly and easily has surfaced. In this paper, we propose a Clustering Framework for crawling and clustering the necessary information from Web pages. The proposed clustering framework consists of three modules: a preprocessing module, clustering module and community module. Using this framework, we are able to automatically cluster Web pages according to topic and rank them in terms of relevance. We describe this framework, and show the results of our preliminary validation work. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1516241.1516319 | ICUIMC |
Keywords | Field | DocType |
clustering module,cluster web page,preprocessing module,efficient clustering framework,available information,relevant web information,community module,necessary information,proposed clustering framework,web page,automated tool,clustering framework,rank,preprocessing,web pages | World Wide Web,Crawling,Web page,Information retrieval,Computer science,Web modeling,Preprocessor,Cluster analysis,Web information,The Internet | Conference |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ok-Ran Jeong | 1 | 181 | 22.02 |
| Sang-Won Lee | 2 | 1536 | 106.03 |