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This paper describes iterative information seeking (IS) as a Markov process during which users advance through states of \u201cnodes\u201d. Nodes are graphic objects on a computer screen that represent both the state of the system and the group of users' or an individual user's degree of confidence in an individual node. After examining nodes to establish a confidence level, the system records the decision as weights affecting the probability of the transition paths between nodes. By training the system in this way, the model incorporates into the underlying Markov process users' decisions as a means to reduce uncertainty. The Markov chain becomes a weighted one whereby the IS makes justified suggestions.<\/jats:p>","DOI":"10.1002\/meet.1450390113","type":"journal-article","created":{"date-parts":[[2005,1,31]],"date-time":"2005-01-31T11:53:14Z","timestamp":1107172394000},"page":"115-123","source":"Crossref","is-referenced-by-count":1,"title":["Weighted Markov chains and graphic state nodes for information retrieval"],"prefix":"10.1002","volume":"39","author":[{"given":"G.","family":"Benoit","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2005,1,31]]},"reference":[{"key":"e_1_2_12_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-3038-0"},{"volume-title":"Applied Probability and Queues","year":"1987","author":"Asmussen S.","key":"e_1_2_12_3_1"},{"key":"e_1_2_12_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/1467-9469.00186"},{"volume-title":"Modern Information Retrieval","year":"1999","author":"Baezer\u2010Yates R.","key":"e_1_2_12_5_1"},{"key":"e_1_2_12_6_1","doi-asserted-by":"crossref","unstructured":"Berger A. &Lafferty J.(1999). 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