Proceedings of the 11th international conference on World Wide Web
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Concept-based interactive query expansion
Proceedings of the 14th ACM international conference on Information and knowledge management
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Fast Random Walk with Restart and Its Applications
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Query suggestions using query-flow graphs
Proceedings of the 2009 workshop on Web Search Click Data
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
The effects of time on query flow graph-based models for query suggestion
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Query reformulation mining: models, patterns, and applications
Information Retrieval
Query suggestions in the absence of query logs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
New assessment criteria for query suggestion
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
DQR: a probabilistic approach to diversified query recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
Efficient fuzzy search in large text collections
ACM Transactions on Information Systems (TOIS)
| Hi-index | 0.00 |
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.