Track: Search
Paper Title:
Causal Relation of Queries from Temporal Logs
Authors:
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 query. 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.
