{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T04:40:26Z","timestamp":1768797626135,"version":"3.49.0"},"reference-count":76,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2014,4,1]],"date-time":"2014-04-01T00:00:00Z","timestamp":1396310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100004316","name":"International Business Machines Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004316","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Early Researcher Award\/Premiers Research Excellence Award"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2014,4]]},"abstract":"<jats:p>\n            Traditionally, in many probabilistic retrieval models, query terms are assumed to be independent. Although such models can achieve reasonably good performance, associations can exist among terms from a human being\u2019s point of view. There are some recent studies that investigate how to model term associations\/dependencies by proximity measures. However, the modeling of term associations theoretically under the probabilistic retrieval framework is still largely unexplored. In this article, we introduce a new concept\n            <jats:italic>cross term<\/jats:italic>\n            , to model term proximity, with the aim of boosting retrieval performance. With cross terms, the association of multiple query terms can be modeled in the same way as a simple unigram term. In particular, an occurrence of a query term is assumed to have an impact on its neighboring text. The degree of the query-term impact gradually weakens with increasing distance from the place of occurrence. We use shape functions to characterize such impacts. Based on this assumption, we first propose a bigram CRoss TErm Retrieval (\n            <jats:italic>CRTER<\/jats:italic>\n            <jats:sub>2<\/jats:sub>\n            ) model as the basis model, and then recursively propose a generalized n-gram CRoss TErm Retrieval (\n            <jats:italic>CRTER<\/jats:italic>\n            <jats:sub>n<\/jats:sub>\n            ) model for n query terms, where\n            <jats:italic>n<\/jats:italic>\n            &gt; 2. Specifically, a bigram cross term occurs when the corresponding query terms appear close to each other, and its impact can be modeled by the intersection of the respective shape functions of the query terms. For an n-gram cross term, we develop several distance metrics with different properties and employ them in the proposed models for ranking. We also show how to extend the language model using the newly proposed cross terms. Extensive experiments on a number of TREC collections demonstrate the effectiveness of our proposed models.\n          <\/jats:p>","DOI":"10.1145\/2590988","type":"journal-article","created":{"date-parts":[[2014,4,23]],"date-time":"2014-04-23T13:52:04Z","timestamp":1398261124000},"page":"1-47","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":47,"title":["Modeling Term Associations for Probabilistic Information Retrieval"],"prefix":"10.1145","volume":"32","author":[{"given":"Jiashu","family":"Zhao","sequence":"first","affiliation":[{"name":"Information Retrieval and Knowledge Management Research Lab, York University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jimmy Xiangji","family":"Huang","sequence":"additional","affiliation":[{"name":"Information Retrieval and Knowledge Management Research Lab, York University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zheng","family":"Ye","sequence":"additional","affiliation":[{"name":"Information Retrieval and Knowledge Management Research Lab, York University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2014,4]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the IEEE International Advance Computing Conference (IACC). 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