Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/54317
Title: An evaluation of page segment recommendation system using user's notes and N-Gram models
Authors: Burin Thunnom
Lachana Ramingwong
Keywords: Computer Science
Engineering
Issue Date: 20-Nov-2015
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.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961783266&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/54317
Appears in Collections:CMUL: Journal Articles

Files in This Item:
There are no files associated with this item.


Items in CMUIR are protected by copyright, with all rights reserved, unless otherwise indicated.