Developing an ontology-supported information recommending system for scholars

Sheng-Yuan Yang, Chun-Liang Hsu, Ssu-Hsien Lu
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引用次数: 4

Abstract

This paper focused on developing an ontology-supported information recommending system for scholars. Not only can it fast integrate specific domain documents, but also it can extract important information from them to take information integration and recommendation ranking. The core technologies include: ontology-supported webpage crawler, webpage classifier, information extractor, information recommender, and a user integration interface. The preliminary experiment outcomes proved that the reliability and validation measurements of the whole system performance can achieve the high-level outcomes of information recommendation.
基于本体的学者信息推荐系统的开发
本文主要研究了基于本体的学者信息推荐系统的开发。它不仅可以快速整合特定领域的文档,而且可以从中提取重要信息进行信息整合和推荐排序。核心技术包括:支持本体的网页爬虫、网页分类器、信息提取器、信息推荐器和用户集成界面。初步实验结果表明,整个系统性能的可靠性和验证性度量可以达到信息推荐的高水平结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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