Akira Karasudani, Satoshi Iwata, Tatsuro Matsumoto, H. Aritake
{"title":"Extracting document relationships by analyzing user's activity history","authors":"Akira Karasudani, Satoshi Iwata, Tatsuro Matsumoto, H. Aritake","doi":"10.1145/2451176.2451208","DOIUrl":null,"url":null,"abstract":"In order to reduce people's workload of looking for valuable information from a large amount of available information, recommendation systems, task management systems, and so on are attracting considerable attention. Such systems are expected to allow easy access to information under the current work context. In the development of these systems, how to handle a user's current work context to know what information he wants to use is a key point. We have developed a novel method to extract relationships among documents as the work context by analyzing the user's activity history according to several viewpoints of a human being who memorizes and seeks information. We report the details of the proposed method, the evaluation result, and an application example.","PeriodicalId":253850,"journal":{"name":"IUI '13 Companion","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IUI '13 Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2451176.2451208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In order to reduce people's workload of looking for valuable information from a large amount of available information, recommendation systems, task management systems, and so on are attracting considerable attention. Such systems are expected to allow easy access to information under the current work context. In the development of these systems, how to handle a user's current work context to know what information he wants to use is a key point. We have developed a novel method to extract relationships among documents as the work context by analyzing the user's activity history according to several viewpoints of a human being who memorizes and seeks information. We report the details of the proposed method, the evaluation result, and an application example.