Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF
Nowadays it is commonly accepted that knowledge, as a resource has become increasingly important in the drive toward knowledge-driven innovation in the manufacturing industry, and which is especially critical for the research and development of complex equipment. In China, there are several fields o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8672769/ |
| _version_ | 1829508895629901824 |
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| author | Linyan Liu Tangxiao Yuan Haojie Song Huifen Wang |
| author_facet | Linyan Liu Tangxiao Yuan Haojie Song Huifen Wang |
| author_sort | Linyan Liu |
| collection | DOAJ |
| description | Nowadays it is commonly accepted that knowledge, as a resource has become increasingly important in the drive toward knowledge-driven innovation in the manufacturing industry, and which is especially critical for the research and development of complex equipment. In China, there are several fields of manufacturing, such as aviation, ship, and electronics. Although each of them has its own professional technology, they also take advantage of the basic common manufacturing technology. Thus, it is meant for sharing manufacturing technology knowledge. In order to promote innovation, a manufacturing technology knowledge retrieval system is developed to make more efficient use of manufacturing technology knowledge. Manufacturing technology knowledge is a phrase with vast meanings, which may include knowledge of different manufacturing process means, machine, and process capabilities or the latest technology developments. In this system, the manufacturing technology knowledge is defined and organized. A knowledge retrieval method based on the weighted fusion of ontology-based semantic extension (OSE) and user-based collaborative filtering (UCF) is proposed and described detailed. On this basis, the prototype system of manufacturing technology knowledge retrieval system is developed. Its architecture and main functions are elaborated. The results of this system facilitate the sharing of manufacturing knowledge, and it is expected to accelerate the process of knowledge transfer, to improve the level of the overall manufacturing technology. |
| first_indexed | 2024-12-16T11:35:42Z |
| format | Article |
| id | doaj.art-07369630bb6041aa88dbe1f7d14f3c51 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T11:35:42Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-07369630bb6041aa88dbe1f7d14f3c512022-12-21T22:33:06ZengIEEEIEEE Access2169-35362019-01-017396233963810.1109/ACCESS.2019.29064228672769Manufacturing Technology Knowledge Retrieval System Based on OSE and UCFLinyan Liu0Tangxiao Yuan1https://orcid.org/0000-0001-6532-6827Haojie Song2Huifen Wang3School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, ChinaSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, ChinaSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, ChinaSchool of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, ChinaNowadays it is commonly accepted that knowledge, as a resource has become increasingly important in the drive toward knowledge-driven innovation in the manufacturing industry, and which is especially critical for the research and development of complex equipment. In China, there are several fields of manufacturing, such as aviation, ship, and electronics. Although each of them has its own professional technology, they also take advantage of the basic common manufacturing technology. Thus, it is meant for sharing manufacturing technology knowledge. In order to promote innovation, a manufacturing technology knowledge retrieval system is developed to make more efficient use of manufacturing technology knowledge. Manufacturing technology knowledge is a phrase with vast meanings, which may include knowledge of different manufacturing process means, machine, and process capabilities or the latest technology developments. In this system, the manufacturing technology knowledge is defined and organized. A knowledge retrieval method based on the weighted fusion of ontology-based semantic extension (OSE) and user-based collaborative filtering (UCF) is proposed and described detailed. On this basis, the prototype system of manufacturing technology knowledge retrieval system is developed. Its architecture and main functions are elaborated. The results of this system facilitate the sharing of manufacturing knowledge, and it is expected to accelerate the process of knowledge transfer, to improve the level of the overall manufacturing technology.https://ieeexplore.ieee.org/document/8672769/Manufacturing technology knowledgeontology-based semantic extensionuser-based collaborative filteringknowledge sharing |
| spellingShingle | Linyan Liu Tangxiao Yuan Haojie Song Huifen Wang Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF IEEE Access Manufacturing technology knowledge ontology-based semantic extension user-based collaborative filtering knowledge sharing |
| title | Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF |
| title_full | Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF |
| title_fullStr | Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF |
| title_full_unstemmed | Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF |
| title_short | Manufacturing Technology Knowledge Retrieval System Based on OSE and UCF |
| title_sort | manufacturing technology knowledge retrieval system based on ose and ucf |
| topic | Manufacturing technology knowledge ontology-based semantic extension user-based collaborative filtering knowledge sharing |
| url | https://ieeexplore.ieee.org/document/8672769/ |
| work_keys_str_mv | AT linyanliu manufacturingtechnologyknowledgeretrievalsystembasedonoseanducf AT tangxiaoyuan manufacturingtechnologyknowledgeretrievalsystembasedonoseanducf AT haojiesong manufacturingtechnologyknowledgeretrievalsystembasedonoseanducf AT huifenwang manufacturingtechnologyknowledgeretrievalsystembasedonoseanducf |