CASIA OpenIR  > 毕业生  > 硕士学位论文
Thesis Advisor戴汝为
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword复杂性 综合集成 人机界面 语义 聚类 语料库 N元模型 推荐系统协作过滤 稀疏问题 冲浪模型 Complexity Metasynthesis Human-machine Interface Semantic Clustering Corpus N-gram Model Recommender System Collaborative Filter
Abstract首先,本文介绍了复杂性科学和综合集成研讨厅体系的理论,解释了为什么综合集成研讨 厅体系是解决复杂问题的途径。其次,基于C/S结构的综合集成研讨厅体系结构,提出了一种会议研讨的软件结构。从软 件工程的角度论述了综合集成研讨厅体系的软件构架、系统描述和运行环境、人机界面设计、 通讯机制、Agent软件设计思想等方面的内容,从而揭示了综合集成研讨厅体系的软件构成。 再次,本文提出了一种新颖的基于大规模标注语料库的词语聚类方法。文中根据专家群体 对某一具体问题进行决策的需要,回顾了国内外几种基于分布的词语聚类方法,并给出我们的算 法原理及实现步骤。首先人工抽取某一类内词语中的几个,从语料库找到这些词的修饰词,组 成修饰词向量,然后对于每一个词语,统计修饰词向量中的每个修饰词和该词语在语料库中同 现的频率,组成特征向量,最后进行聚类分析。支持宏观经济决策的试验表明该算法能有效地 实现词语的聚类。 最后,本文还参与提出了一种利用WWW冲浪模型,模仿用户访问Web页过程中的一些特 点规律,并将用户的冲浪过程延续,模拟用户在Web站点访问更多的Web页,从而估计出用户 对更多’Web页的评价。本文还给出了实验比较,表明扩展冲浪深度后,系统推荐Web页的效果 得到明显提高。
Other AbstractThe theory of Complexity Science and Hall for Workshop of Metasynthetic Engineering (HWME) is firstly summarized in this paper. The reason why HWME is a solution to complicated problems is discussed in succession. Based on C/S software structure, this paper proposes a software structure of meeting-discussion, in order to reduce the shortness of B/S software structure. From the viewpoint of software engineering, this paper describes the software structure, system description and running environment, human-machine interface, communication proxy, agent-oriented software design of HWME, thus reveals the software system of HWME. This paper proposes a novel approach for word clustering based on large tagged corpus. According to the need of decision-making support for a specific problem, this paper review several algorithms developed by previous works, after that, our algorithm is rendered. Firstly, we manually extract several words from a specified class, and then search the corpus for the modifiers of those words to construct modifier vector, for each of other words, count the frequency of its co-occurrence with each modifier in the modifier vector to construct its characteristic vector, finally, apply clustering algorithm to those characteristic vectors to get the result. Proved by experiment carried out on Decision-making Support for Macro Economics, this algorithm is effective for word clustering. This paper also proposes a surfing model, by utilizing the regularity of the user's previous visiting or rating, virtually extending the user's surfing length in the Web site, so more document has been rated or visited, and thus we can get a impact user-page matrix. We present experimental results that show how this approach performs better than the former.
Other Identifier711
Document Type学位论文
Recommended Citation
GB/T 7714
康铁钢. 综合集成研讨厅的系统实现与算法研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2003.
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