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[1E3-GS-6-03] Information Recommendation based on Paper Contents
Keywords:text mining, information recommendation
In research and development, previous works are useful for surveying technical methods. However, in the recent information explosion era, the number of papers that individual researchers can carefully read is limited, and it is difficult to comprehensively collect information. Recently, open-access archive (such as arXiv.org) for academic articles have been paid attention, and have become useful knowledge sources both in quality and quantity. Based on the knowledge source, it would be very useful if technical information such as ideas and algorithms could be referred to from a large number of research in specific fields. Therefore, in this research, we proposed an information recommendation technique that recommends reference information for target problems using paper contents as a knowledge source. As a result, in experimental evaluation with a large-scale paper archive, we confirmed the effectiveness of the proposed method.
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