An exploration of axiomatic approaches to information retrieval Export

@inproceedings{FangZhai05AximoaticRetrieal, abstract = {Existing retrieval models generally do not offer any guarantee for optimal retrieval performance. Indeed, it is even difficult, if not impossible, to predict a model's empirical performance analytically . This limitation is at least partly caused by the way existing retrieval models are developed where relevance is only coarsely modeled at the level of documents and queries as opposed to a finer granularity level of terms. In this paper, we present a new axiomatic approach to developing retrieval models based on direct modeling of relevance with formalized retrieval constraints defined at the level of terms. The basic idea of this axiomatic approach is to search in a space of candidate retrieval functions for one that can satisfy a set of reasonable retrieval constraints. To constrain the search space, we propose to define a retrieval function inductively and decompose a retrieval function into three component functions. Inspired by the analysis of the existing retrieval functions with the inductive definition, we derive several new retrieval functions using the axiomatic retrieval framework. Experiment results show that the derived new retrieval functions are more robust and less sensitive to parameter settings than the existing retrieval functions with comparable optimal performance.}, address = {New York, NY, USA}, author = {Fang, Hui and Zhai, Chengxiang}, booktitle = {SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval}, citeulike-article-id = {1233217}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1076116}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1076034.1076116}, doi = {10.1145/1076034.1076116}, isbn = {1-59593-034-5}, keywords = {axiomatic, information, retrieval, term, weighting}, location = {Salvador, Brazil}, pages = {480--487}, posted-at = {2009-08-24 16:40:16}, priority = {4}, publisher = {ACM}, title = {An exploration of axiomatic approaches to information retrieval}, url = {http://dx.doi.org/10.1145/1076034.1076116}, year = {2005} }

TY - CONF ID - FangZhai05AximoaticRetrieal L3 - citeulike-article-id:1233217 N2 - Existing retrieval models generally do not offer any guarantee for optimal retrieval performance. Indeed, it is even difficult, if not impossible, to predict a model's empirical performance analytically . This limitation is at least partly caused by the way existing retrieval models are developed where relevance is only coarsely modeled at the level of documents and queries as opposed to a finer granularity level of terms. In this paper, we present a new axiomatic approach to developing retrieval models based on direct modeling of relevance with formalized retrieval constraints defined at the level of terms. The basic idea of this axiomatic approach is to search in a space of candidate retrieval functions for one that can satisfy a set of reasonable retrieval constraints. To constrain the search space, we propose to define a retrieval function inductively and decompose a retrieval function into three component functions. Inspired by the analysis of the existing retrieval functions with the inductive definition, we derive several new retrieval functions using the axiomatic retrieval framework. Experiment results show that the derived new retrieval functions are more robust and less sensitive to parameter settings than the existing retrieval functions with comparable optimal performance. CY - Salvador, Brazil SN - 1-59593-034-5 AD - New York, NY, USA EP - 487 TI - An exploration of axiomatic approaches to information retrieval PB - ACM T2 - SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval SP - 480 KW - axiomatic KW - information KW - retrieval KW - term KW - weighting AU - Fang, Hui AU - Zhai, Chengxiang PY - 2005/// UR - http://dx.doi.org/10.1145/1076034.1076116 ER -