Name
Abstract | ||
|---|---|---|
The rapid increase of the information on the World Wide Web (WWW) makes it challenging to extract the relevant information utilizing the reasonable amount of resources. Most of the time, it become necessary for users to modify their search queries several times before they obtain the necessary information. Certainly there are various ways to circumvent this problem up to a certain extent. However, most of those approaches do not consider the searching behavior of the end users. A wide spectrum of research is on its way to personalize the web search results to meet the user needs. Therefore, we are proposing an algorithm to generate a hierarchical structure to extract the general user search patterns identified based on the randomly selected seed word and queries. In other words, we propose grouping user queries semantically to form what we refer to as "super concepts" composed of related queries. Our results indicate significant improvement in retrieval effectiveness by utilizing the generic behavioral patterns. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1233341.1233423 | ACM Southeast Regional Conference 2005 |
Keywords | Field | DocType |
web search result,end user,user session context,hierarchical structure,general user search pattern,user need,relevant information,certain extent,necessary information,generic behavioral pattern,world wide web,concept set extraction,spectrum | Data mining,Behavioral pattern,World Wide Web,Search engine,End user,Information retrieval,Semantic search,Computer science,Web navigation,Concept extraction | Conference |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hemant Joshi | 1 | 37 | 5.74 |
| Shinya Ito | 2 | 0 | 0.68 |
| Santhosh Kanala | 3 | 0 | 0.34 |
| Sangeetha Hebbar | 4 | 0 | 0.34 |
| Coşkun Bayrak | 5 | 197 | 26.47 |