Ranieri Baraglia
Carlos Castillo
Debora Donato
Franco Maria Nardini
Raffaele Perego
Fabrizio Silvestri
ABSTRACT
World Wide Web content continuously grows in size and importance. Furthermore, users ask Web search engines to satisfy increasingly disparate information needs. New techniques and tools are constantly developed aimed at assisting users in the interaction with the Web search engine. Query recommender systems suggesting interesting queries to users are an example of such tools. Most query recommendation techniques are based on the knowledge of the behaviors of past users of the search engine recorded in query logs.
A recent query-log mining approach for query recommendation is based on Query Flow Graphs (QFG). In this paper we propose an evaluation of the effects of time on this query recommendation model. As users interests change over time, the knowledge extracted from query logs may suffer an aging effect as new interesting topics appear. In order to validate experimentally this hypothesis, we build different query flow graphs from the queries belonging to a large query log of a real-world search engine. Each query flow graph is built on distinct query log segments. Then, we generate recommendations on different sets of queries. Results are assessed both by means of human judgments and by using an automatic evaluator showing that the models inexorably age.
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Digital Library
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Index Terms
- Aging effects on query flow graphs for query suggestion
Recommendations
The query-flow graph: model and applications
CIKM '08: Proceedings of the 17th ACM conference on Information and knowledge managementQuery 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. ...
The effects of time on query flow graph-based models for query suggestion
RIAO '10: Adaptivity, Personalization and Fusion of Heterogeneous InformationA recent query-log mining approach for query recommendation is based on Query Flow Graphs, a markov-chain representation of the query reformulation process followed by users of Web Search Engines trying to satisfy their information needs. In this paper ...
Visual query suggestion: Towards capturing user intent in internet image search
Query suggestion is an effective approach to bridge the Intention Gap between the users' search intents and queries. Most existing search engines are able to automatically suggest a list of textual query terms based on users' current query input, which ...
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