面向个性化Web信息采集的本体挖掘

Xiaohui Tao, Yuefeng Li, N. Zhong, R. Nayak
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引用次数: 140

摘要

人们普遍认为本体对于个性化的Web信息收集非常有用。然而,在单个计算模型中使用“kind-of”、“part-of”和“related-to”的语义关系并综合常识和专家知识是一项挑战。本文提出了一种个性化的本体模型,试图解决这一问题。并提出了一种二维(穷竭性和专一性)方法,在单一框架中定量分析这些语义关系。通过将该模型应用于Web信息收集系统,成功地对提案进行了评估。该模型对Web智能中个性化本体工程和基于概念的Web信息收集有重要贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology Mining for Personalized Web Information Gathering
It is well accepted that ontology is useful for personalized Web information gathering. However, it is challenging to use semantic relations of "kind-of", "part-of", and "related-to" and synthesize commonsense and expert knowledge in a single computational model. In this paper, a personalized ontology model is proposed attempting to answer this challenge. A two-dimensional (Exhaustivity and Specificity) method is also presented to quantitatively analyze these semantic relations in a single framework. The proposals are successfully evaluated by applying the model to a Web information gathering system. The model is a significant contribution to personalized ontology engineering and concept-based Web information gathering in Web Intelligence.
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