Name
Abstract | ||
|---|---|---|
In this paper, we show that most multiple term queries include more than one topic and users usually reformulate their queries by topics instead of terms. In order to provide empirical evidence on user's reformulation behavior and to help search engines better handle the query reformulation problem, we focus on detecting internal topics in the original query and analyzing users. reformulation to those topics. Particularly, we utilize the Interaction Information (II) to measure the degree of one sub-query being a topic based on the local search results. The experimental results on query log show that: most users reformulate query at the topical level; and our proposed II-based algorithm is a good method to detect topics from original queries. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1242572.1242758 | WWW |
Keywords | Field | DocType |
local search result,multiple term query,reformulation behavior,query log show,internal topic,original query,interaction information,search engine,query reformulation problem,users reformulate query,query topic detection,empirical evidence,local search | Query optimization,Web search query,Data mining,World Wide Web,Query language,Query expansion,Information retrieval,Computer science,Sargable,Web query classification,Spatial query,Interaction information | Conference |
Citations | PageRank | References |
6 | 0.46 | 2 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xuefeng He | 1 | 6 | 0.46 |
| Jun Yan | 2 | 1798 | 85.25 |
| Jinwen Ma | 3 | 841 | 74.65 |
| Ning Liu | 4 | 253 | 15.62 |
| Zheng Chen | 5 | 5019 | 256.89 |