The query-flow graph: model and applications
Source:
Conference on Information and Knowledge Management (CIKM), ACM, Napa Valley, CA, USA, p.609-618 (2008)
Abstract:
Query logs record the queries and the actions of the users of search
engines, and as such they contain valuable information about the
interests, the preferences, and the behavior of the users, as well as
their implicit feedback to search-engine results.
Mining the wealth of information available in the query logs has many
important applications including query-log analysis, user profiling
and personalization, advertising, query recommendation, and more.
The query-flow graph is an outcome of query-log mining and, at the same
time, a useful tool for it.
We propose a methodology that builds such a graph by mining time and
textual information as well as aggregating queries from different
users.
Using this approach we build a real-world query-flow graph
from a large-scale query log, and we demonstrate its utility in
concrete applications, namely, finding logical sessions,
and query recommendation. We believe, however, that the usefulness of
the query-flow graph goes beyond these two applications.
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