一种基于语义可理解的信息过滤算法

张波; 向阳; 王坚

doi:10.3724/SP.J.1146.2009.01393

一种基于语义可理解的信息过滤算法

doi: 10.3724/SP.J.1146.2009.01393

基金项目:

国家863计划项目(2008AA04Z106)，国家自然科学基金(70771077)，上海市科委制造业信息化专项基金(08DZ1122300)和上海信息化发展专项资金 (200901015)资助课题

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出版历程
- 收稿日期: 2009-10-29
- 修回日期: 2010-07-08
- 刊出日期: 2010-10-19

Information Filtering Algorithm Based on Semantic Understanding

摘要

摘要: 个性化与准确化是信息过滤技术发展面临的关键问题。语义理解技术有助于解决这一关键问题。其基本思想是对信息内容以及用户需求进行形式化语义描述，使其具备计算机可理解的形式，进而以语义为标准实现信息过滤。该文提出定义信息领域本体以描述语义，并将信息语义分为信息特征项和其解释，同时将用户需求语义分为显性需求和隐性需求。进而，给出了信息语义理解判定方法和用户需求语义理解判定方法。最后，该文提出了基于语义可理解的信息过滤算法。实验分析表明，这种信息过滤方式能够有效地提高信息获取的效率。
- 信息处理 /
- 信息过滤 /
- 语义 /
- 语义可理解 /
- 信息领域本体
Abstract: Personalization and accuracy are the key issues for the development information filtering. Research on semantics understanding will help solve the issues. The basic idea is to describe the semantics of information content and user requirements formally so that computer would understand the formal semantics. Then the semantics would be criterion for information filtering. In this paper information domain ontology is defined to describe semantics. Information semantics is composed by information feature terms and their explanations, and user requirements semantics is represented by definite requirements and latent requirements. Furthermore, the judging methods of information semantics understanding and user requirement semantic understanding are proposed. Finally, this paper presents the information filtering algorithm based on semantic understanding. Experiments show that the information filtering algorithm is effective and feasible.
- Information processing /
- Information filtering /
- Semantics /
- Semantics understanding /
- Information domain ontology

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参考文献(1)

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