Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al].
The paper aims to propose cooperative reading, which is a reading support technique that allows library users to help each other. To achieve cooperative reading, it is necessary for a user to discover others with similar interests. Therefore, this paper also aims to develop and evaluate a recommenda...
| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2011
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/3563/1/K_MAO%20TSUNEKAWA%20A-LIEP%20IM%2011.pdf |
| _version_ | 1825733722485293056 |
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| author | Tsunekawa, Mao Ono, Haruki Konishi, Kyoji Tsuji, Keita Matsumura, Atsushi Uda, Norihiko |
| author_facet | Tsunekawa, Mao Ono, Haruki Konishi, Kyoji Tsuji, Keita Matsumura, Atsushi Uda, Norihiko |
| author_sort | Tsunekawa, Mao |
| collection | UITM |
| description | The paper aims to propose cooperative reading, which is a reading support technique that allows library users to help each other. To achieve cooperative reading, it is necessary for a user to discover others with similar interests. Therefore, this paper also aims to develop and evaluate a recommendation function that recommends similar users using Nippon Decimal Classification (NDC) Tree Profiling. Is the user recommendation using NDC Tree Profiling effective in finding similar users? Which parameter of NDC Tree Profiling method is the most effective expression of users‘ interests? We developed the Shizuku2.0 system to support the creation of a library user community in which users help each other efficiently and mutually. We also designed and developed NDC Tree Profiling, which enables the creation of library user profiles, for the purposes of the user recommendation mechanism. To verify the effect of the user recommendation mechanism, we performed an experiment with 37 student users to calculate recall and precision. We found that the recommendation using NDC Tree Profiling is more effective than a random recommendation. However, we also recognized that there is room for improvement relative to a past information recommendation technique. Moreover, we found the second level of the NDC code could be the most effective expression of users‘ interests. In the discussion of the optimization of parameters, we propose a new way of implementing the NDC Tree, based on the second division of NDC, which is expected to improve creation of user profiles. |
| first_indexed | 2024-03-06T01:21:19Z |
| format | Conference or Workshop Item |
| id | oai:ir.uitm.edu.my:3563 |
| institution | Universiti Teknologi MARA |
| language | English |
| last_indexed | 2024-03-06T01:21:19Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oai:ir.uitm.edu.my:35632019-06-20T07:12:04Z https://ir.uitm.edu.my/id/eprint/3563/ Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. Tsunekawa, Mao Ono, Haruki Konishi, Kyoji Tsuji, Keita Matsumura, Atsushi Uda, Norihiko Library Science. Information Science The paper aims to propose cooperative reading, which is a reading support technique that allows library users to help each other. To achieve cooperative reading, it is necessary for a user to discover others with similar interests. Therefore, this paper also aims to develop and evaluate a recommendation function that recommends similar users using Nippon Decimal Classification (NDC) Tree Profiling. Is the user recommendation using NDC Tree Profiling effective in finding similar users? Which parameter of NDC Tree Profiling method is the most effective expression of users‘ interests? We developed the Shizuku2.0 system to support the creation of a library user community in which users help each other efficiently and mutually. We also designed and developed NDC Tree Profiling, which enables the creation of library user profiles, for the purposes of the user recommendation mechanism. To verify the effect of the user recommendation mechanism, we performed an experiment with 37 student users to calculate recall and precision. We found that the recommendation using NDC Tree Profiling is more effective than a random recommendation. However, we also recognized that there is room for improvement relative to a past information recommendation technique. Moreover, we found the second level of the NDC code could be the most effective expression of users‘ interests. In the discussion of the optimization of parameters, we propose a new way of implementing the NDC Tree, based on the second division of NDC, which is expected to improve creation of user profiles. 2011 Conference or Workshop Item PeerReviewed text en https://ir.uitm.edu.my/id/eprint/3563/1/K_MAO%20TSUNEKAWA%20A-LIEP%20IM%2011.pdf Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. (2011) In: Proceedings of the Asia-Pacific Conference On Library & Information Education & Practice 2011 (A-LIEP2011), 22-24 June 2011, Putrajaya, Malaysia. |
| spellingShingle | Library Science. Information Science Tsunekawa, Mao Ono, Haruki Konishi, Kyoji Tsuji, Keita Matsumura, Atsushi Uda, Norihiko Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title | Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title_full | Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title_fullStr | Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title_full_unstemmed | Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title_short | Shizuku2.0: Cooperative reading support system / Mao Tsunekawa, Haruki Ono, Kyoji Konishi... [et.al]. |
| title_sort | shizuku2 0 cooperative reading support system mao tsunekawa haruki ono kyoji konishi et al |
| topic | Library Science. Information Science |
| url | https://ir.uitm.edu.my/id/eprint/3563/1/K_MAO%20TSUNEKAWA%20A-LIEP%20IM%2011.pdf |
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