Name
Abstract | ||
|---|---|---|
In this paper, we study a new problem of mining causal relation of queries in search engine query logs. Causal relation between two queries means event on one query is the causation of some event on the other. We first detect events in query logs by efficient statistical frequency threshold. Then the causal relation of queries is mined by the geometric features of the events. Finally the Granger Causality Test (GCT) is utilized to further re-rank the causal relation of queries according to their GCT coefficients. In addition, we develop a 2-dimensional visualization tool to display the detected relationship of events in a more intuitive way. The experimental results on the MSN search engine query logs demonstrate that our approach can accurately detect the events in temporal query logs and the causal relation of queries is detected effectively. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1145/1242572.1242735 | WWW |
Keywords | Field | DocType |
temporal query log,msn search engine query,2-dimensional visualization tool,causal relation,temporal log,gct coefficient,query log,efficient statistical frequency threshold,granger causality test,search engine query log,mining causal relation,time series,2 dimensional,search engine | Data mining,Search engine,Information retrieval,Causal relations,Visualization,Computer science,Granger causality,Causation,Frequency,Spatial query | Conference |
Citations | PageRank | References |
9 | 0.58 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yizhou Sun | 1 | 3446 | 143.93 |
| Kunqing Xie | 2 | 640 | 46.64 |
| Ning Liu | 3 | 253 | 15.62 |
| Shuicheng Yan | 4 | 263 | 12.12 |
| Benyu Zhang | 5 | 2135 | 90.41 |
| Zheng Chen | 6 | 5019 | 256.89 |