Search the web x.0: mining and recommending web-mediated processes
Proceedings of the third ACM conference on Recommender systems
Modeling and predicting the task-by-task behavior of search engine users
Proceedings of the 10th Conference on Open Research Areas in Information Retrieval
Discovering tasks from search engine query logs
ACM Transactions on Information Systems (TOIS)
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"History Teaches Everything, Including the Future", wrote Alphonse de Lamartine in the nineteen century. Even if history cannot be really considered a predictive science, historical information can successfully be used in many fields. This paper deals with Web Search Engines and their Query logs, which contain historical information about past usage of such systems. We will present some of the most interesting results obtained in this field by the High Performance Computing Lab in Pisa in collaboration with Research Labs worldwide. The techniques reviewed are mainly focused on enhancing the efficiency of large-scale distributed search systems.