Ontology-Supported Web Recommender for Scholar Information

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

Abstract

In this quickly developed and shifting era of Internet, how to make use of webpage indexing structure or search engines which let information demanders fast and precisely search and extract out advantage information has become extremely important capability in users on the Web. This paper combined a data mining tool SPSS Clementine with the domain ontology to mine out usefully important information from huge datum, and then to employ Java to develop an information recommender for scholars--- Onto Recommender, in which can recommend suitably important information to scholars. The preliminary experiment outcomes proved the reliability and validation of the recommender achieving the regular-level outcomes of information recommendation, and accordingly proved the feasibility of the related techniques proposed in this paper.
本体支持的学者信息网络推荐
在这个快速发展和变化的互联网时代,如何利用网页索引结构或搜索引擎,让信息需求者快速、准确地搜索和提取优势信息,已经成为网络用户极其重要的能力。本文将数据挖掘工具SPSS Clementine与领域本体相结合,从海量数据中挖掘出有用的重要信息,然后利用Java开发了一个面向学者的信息推荐器——Onto recommender,可以向学者推荐合适的重要信息。初步实验结果证明了推荐器实现信息推荐的规则级结果的可靠性和有效性,从而证明了本文提出的相关技术的可行性。
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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