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This will enable the return of temporally relevant documents, thus providing a temporal overview of the results in the form of timeliness or similar structures. Oliveira (Eds.), In Lecture Notes in Computer Science - SPIRE2002: 9th International Symposium on String Processing and Information Retrieval (Vol.

It also shows to be very useful for query understanding, query disambiguation, query classification, result diversification and so on.

One can provide many examples when the returned search results are of little value due to temporal problems such as obsolete data on weather, outdated information about a given company’s earnings or information on already-happened or invalid predictions.

Pinto (Eds.), Lecture Notes in Artificial Intelligence - Progress in Artificial Intelligence - EPIA2011: 15th Portuguese Conference on Artificial Intelligence associated to APPIA: Portuguese Association for Artificial Intelligence (Vol.

Detecting Seasonal Queries by Time-Series Analysis. In SIGIR2011: In Proceedings of the 34th international ACM SIGIR conference on Research and development in Information (pp.

In ENIR 2011: Proceedings of the Enriching Information Retrieval Workshop associated to SIGIR2011: 34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

The Web Changes Everything: Understanding the Dynamics of Web Content.

In SIGIR 2009: Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (pp.

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