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dc.contributor.authorBurin Thunnomen_US
dc.contributor.authorLachana Ramingwongen_US
dc.date.accessioned2018-09-04T10:11:46Z-
dc.date.available2018-09-04T10:11:46Z-
dc.date.issued2015-11-20en_US
dc.identifier.other2-s2.0-84961783266en_US
dc.identifier.other10.1109/ICIEV.2015.7333990en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961783266&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/54317-
dc.description.abstract© 2015 IEEE. Web content searching is a daily activity of almost everyone. Often, it occurs several times a day. A number of people need to make sense out of a huge amount of webpages in order to complete their jobs. Many others also have to rely on it. A number of research works in sensemaking have demonstrated the needs for supporting tools in web content searching. In this paper, NorCost, a system that recommends relevant page segments, is proposed. The system emphasizes helping people to complete their sensemaking tasks without having to go through every detail of the webpage themselves as such tasks could takes long time to finish. The evaluation of NorCost is carried out to assess its accuracy as well as time taken to process the recommendation.en_US
dc.subjectComputer Scienceen_US
dc.subjectEngineeringen_US
dc.titleAn evaluation of page segment recommendation system using user's notes and N-Gram modelsen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2015 4th International Conference on Informatics, Electronics and Vision, ICIEV 2015en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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