{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:28:30Z","timestamp":1740202110311,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>This paper describes a method for discovering URLs with contextually relevant deep-topics, and then propagating such information to collaborating users lacking such information. When a user is knowledgeable about a subject, their reasons for frequently browsing a URL extend beyond the fact that it is merely related to said subject. This paper's method includes an algorithm for discovering the surface-topic of a URL, and the underlying deep-topic that a user is truly interested in with respect to a given URL. The deep-topic extraction process works by using URLs linked together through a user's behavioral browsing patterns in order to discover the surface or group-topic of surrounding URLs, and then subtracting those topics to discover hidden deeper topics. This paper describes the three parts of the method: Information Extraction, Propagation, and Verification &amp;amp; Integration, which together form a method with high levels of parallelism due to its distributed and independent nature. This paper also discusses concrete usage-scenarios for the included method, and data structures which would support the implementation of this paper's method.<\/jats:p>","DOI":"10.3233\/978-1-61499-361-2-146","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:26:53Z","timestamp":1740133613000},"source":"Crossref","is-referenced-by-count":0,"title":["Identifying and Propagating Contextually Appropriate Deep-Topics amongst Collaborating Web-Users"],"prefix":"10.3233","author":[{"family":"Hall Jeremy","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Kiyoki Yasushi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Modelling and Knowledge Bases XXV"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:29:48Z","timestamp":1740137388000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=260&spage=146"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-361-2-146","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2014]]}}}