An evaluation of page segment recommendation system using user's notes and N-Gram models
© 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...
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th-cmuir.6653943832-543172018-09-04T10:14:19Z An evaluation of page segment recommendation system using user's notes and N-Gram models Burin Thunnom Lachana Ramingwong Computer Science Engineering © 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. 2018-09-04T10:11:46Z 2018-09-04T10:11:46Z 2015-11-20 Conference Proceeding 2-s2.0-84961783266 10.1109/ICIEV.2015.7333990 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961783266&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54317 |
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Computer Science Engineering Burin Thunnom Lachana Ramingwong An evaluation of page segment recommendation system using user's notes and N-Gram models |
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© 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. |
format |
Conference Proceeding |
author |
Burin Thunnom Lachana Ramingwong |
author_facet |
Burin Thunnom Lachana Ramingwong |
author_sort |
Burin Thunnom |
title |
An evaluation of page segment recommendation system using user's notes and N-Gram models |
title_short |
An evaluation of page segment recommendation system using user's notes and N-Gram models |
title_full |
An evaluation of page segment recommendation system using user's notes and N-Gram models |
title_fullStr |
An evaluation of page segment recommendation system using user's notes and N-Gram models |
title_full_unstemmed |
An evaluation of page segment recommendation system using user's notes and N-Gram models |
title_sort |
evaluation of page segment recommendation system using user's notes and n-gram models |
publishDate |
2018 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84961783266&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/54317 |
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