An improved method based on vector-space model for integration of heterogeneous itembanks
碩士 === 國立成功大學 === 電腦與通信工程研究所 === 97 === Lately, Automated Document Categorization has been used in many fields. For example, Information Retrieval, Data Mining, Artificial Intelligence, Natural Language Processing, E-Learning, etc. Digital content becomes huge by the quick development of E-Learning....
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| Format: | Others |
| Language: | zh-TW |
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2009
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| Online Access: | http://ndltd.ncl.edu.tw/handle/14841204960617767101 |
| Summary: | 碩士 === 國立成功大學 === 電腦與通信工程研究所 === 97 === Lately, Automated Document Categorization has been used in many fields. For example, Information Retrieval, Data Mining, Artificial Intelligence, Natural Language Processing, E-Learning, etc. Digital content becomes huge by the quick development of E-Learning. Because the content providers have different views to the similar learning objects, the schemas of the content is different. This is the difficulty of integration of digital content. Adaptive learning is a trend in E-Learning. Adaptive learning (personalization) focuses on providing the different Digital content with different learners and their situation. For the purpose above, Assessment can be a common tool to realize the status of learning. The effectiveness of automatic learning assessment depends on the Itembanks. This thesis focuses on the Sociality course and Nature course of elementary schools in Taiwan. We use the technology of Vector Space Model(VSM) and Latent Semantic Indexing(LSI) to integrate the different Itembanks from different provider.
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