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Return to Session I: Opening session
A key missing component in information retrieval systems is self-diagnostic tests to establish whether the system can provide reasonable results for a given query on a document collection. If we can measure properties of a retrieved set of documents which allow us to predict average precision, we can automate the decision of whether to elicit relevance feedback, or modify the retrieval system in other ways. We use meta-data attached to documents in the form of time stamps to measure the distribution of documents retrieved in response to a query, over the time domain, to create a temporal profile for a query. We define some useful features over this temporal profile. We find that using these temporal features, together with the content of the documents retrieved, we can improve the prediction of average precision for a query.
@inproceedings{1008998, author = {Fernando Diaz and Rosie Jones}, title = {Using temporal profiles of queries for precision prediction}, booktitle = {SIGIR '04: Proceedings of the 27th annual international conference on Research and development in information retrieval}, year = {2004}, isbn = {1-58113-881-4}, pages = {18--24}, location = {Sheffield, United Kingdom}, doi = {http://doi.acm.org/10.1145/1008992.1008998}, publisher = {ACM Press}, }  ©2005 Association for Computing Machinery |
