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Application of Case-Based Reasoning to Intelligent Support System for Coordinating Land Conflicts

Journal of Southwest Jiaotong University(English Edition) 2007年第3期15卷 210-217页

作者：李红波谭术魁钟海峰 School of Civil Engineering and Mechanics Huazhong University of Science and Technology School of Computer Science and Engineering Huazhong University of Science and Technology

To establish the institutional mechanism for land conflict coordination in China, a case-based reasomng system is developed as an intelligent support and effective manner to resolve such issues. The establishment of the case library is discussed, previous land conflict cases are archived in a structural representation format for retrieval, and the similarity algorithm is adopted to compare the case features. Group tests show a good classification performance, which reveals that the system is feasible.

关键词： Land conflict Case-based reasoning similarity algorithm Coordination system

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The reflection of hierarchical cluster analysis of co-occurrence matrices in SPSS

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Chinese Journal of Library and Information Science 2015年第2期 11-24页

作者： Qiuju ZHOU Fuhai LENG Loet LEYDESDORFF National Science Library Chinese Academy of Sciences University of Amsterdam Amsterdam School of Communication Research (ASCo R) PO Box 15793 1001 NG Amsterdam the Netherlands

Purpose： To discuss the problems arising from hierarchical cluster analysis of co-occurrence matrices in SPSS, and the corresponding solutions. Design/methodology/approach： We design different methods of using the SPSS hierarchical clustering module for co-occurrence matrices in order to compare these methods. We offer the correct syntax to deactivate the similarity algorithm for clustering analysis within the hierarchical clustering module of SPSS. Findings： When one inputs co-occurrence matrices into the data editor of the SPSS hierarchical clustering module without deactivating the embedded similarity algorithm, the program calculates similarity twice, and thus distorts and overestimates the degree of similarity. Practical implications： We offer the correct syntax to block the similarity algorithm for clustering analysis in the SPSS hierarchical clustering module in the case of co-occurrence matrices. This syntax enables researchers to avoid obtaining incorrect results. Originality/value： This paper presents a method of editing syntax to prevent the default use of a similarity algorithm for SPSS＇s hierarchical clustering module. This will help researchers, especially those from China, to properly implement the co-occurrence matrix when using SPSS for hierarchical cluster analysis, in order to provide more scientific and rational results.

关键词： Co-occurrence matrices Hierarchical cluster analysis SPSS similarity algorithm The syntax editor

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A Framework for Hoax News Detection and Analyzer used Rule-based Methods

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2019年第10期10卷 402-408页

作者： Yuliani, S. Y. Bin Abdollah, Mohd Faizal Sahib, Shahrin Wijaya, Yunus Supriadi Univ Tekn Malaysia Melaka Fac Informat Commun Technol Informat Secur & Networking Res Grp InFORSNET Melaka Malaysia Widyatma Univ Bandung Indonesia Univ Tekn Malaysia Melaka Fac Informat Commun Technol Informat Secur & Networking Res Melaka Malaysia Telkom Univ Informat Dept Bandung Indonesia

Currently, the era where social media can present various facilities can answer the needs of the community for information and utilization for socio-economic interests. But the other impact of the presence of social media opens an ample space for the existence of information or hoax news about an event that is troubling the public. The hoax also provides cynical provocation, which is inciting hatred, anger, incitement to many people, directly influencing behavior so that it responds as desired by the hoax makers. Fake news is playing an increasingly dominant role in spreading Misinformation by influencing people's Perceptions or knowledge to distort their awareness and decision-making. A framework is develope dataset collection of hoax gathered using web crawlers from several websites, using classification techniques. This hoax news will be categorized into several detection parameters including, page URL, title hoax news, publish date, author, and content. Matching each word hoax using the similarity algorithm to produce the accuracy of the hoax news uses the rule-based detection method. Experiments were carried out on eleven thousand-hoax news used as training datasets and testing data sets;this data set for validation using similarity algorithms, to produce the highest accuracy of hoax text similarity. In this study, each hoax news will label into four categories, namely, Fact, Hoax, Information, Unknown. Contributions propose Automatic detection of hoax news, Automatic Multilanguage Detection, and a collection of datasets that we gather ourselves and validation that results in four categories of hoax news that have measured in terms of text similarity using similarity techniques. Further research can be continued by adding objects hate speech, black campaign, blockchain technique to ward off hoaxes, or can produce algorithms that produce better text accuracy.

关键词： Component hoax news framework web crawling detection multilanguage unsupervised algorithm similarity algorithm

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A Distance Education Helper Matching Model Based on Multi-agent

A Distance Education Helper Matching Model Based on Multi-ag...

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2012 International Conference on Computer,Control,Education and Management(CCEM 2012)

作者： Yan Lian-duo Tian Xiu-hong Jin Chang-hui Department of Ideological and Political Hebei Normal University of Science & Technology Academic Affairs Office Hebei Normal University of Science & Technology

In the distance education platform, it is an important topic that how to intelligently help learner to find right helperTo address the problem, a set of matching model of problem and helper based on problem similarity under mutual learning system environment was presented with multi-agent technologyThe model introduces concept of problem gathering, namely to determine similarity between helper and problem by computing similarity among many problems and proposed problemsBy returning helper agent that has many similarities with proposed problem, the circumstance of non-relevance between matching problem and proposed problem can be avoidedMeanwhile, the concept of valid problem number, valid matching problem number and average similarity of valid matching problem, it can ensure effectively solving problem of helper matchingExperiment results show that the helper matching model can achieve ideal matching effect1Introduction

关键词： Multi-Agent similarity algorithm Mutual Learning Helper Matching Model

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Research on User Preference Diffusion and Information Recommendation Based on Ontology and Information Fusion

Research on User Preference Diffusion and Information Recomm...

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第七届工程管理国际学术研讨会

作者： Xuewei LI Shi YING Wei HONG School of information management Wuhan University School of Computer Science Wuhan University College of Sports Engineering and Information Technology Wuhan Sport University

Personalized recommendation method is one of the representative solutions to solve the contradiction between information diversification and user demand specificity. Due to the limitations of the algorithm and the difficulty of item feature extraction, the recommendation results of content-based recommendation system are too specialized to provide users with novel recommendation items. This paper tries to find a method of interest and preference diffusion to improve the recommendation specialization. In this paper, a comprehensive recommendation method based on information hierarchy distance and information loss distance in domain ontology is proposed. This method comprehensively calculates the similarity between items through similarity algorithms based on information hierarchy distance and information loss distance. The research shows that: the information loss distance in the domain ontology can have a great impact on the recommendation results, and the comprehensive recommendation method based on the information hierarchy distance and information loss distance can effectively improve the diversity and usefulness of the recommendation results.

关键词： similarity algorithm User preference diffusion Personalized recommendation Information fusion Ontology

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A Clustering algorithm of No-Word-Segmentation for Chinese Search Engine Results

A Clustering Algorithm of No-Word-Segmentation for Chinese S...

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2007年第三届语义和知识网格国际会议(Third International Conference on Semantics,Knowledge,and Grid)(SKG 2007)

作者： Deqing Wang Hui Zhang Liping Zhao Ke Xie Beihang University State Key Lab of Software Development Environment Beijing 100083

Along with information on the Internet increasing dramatically, People usually search and locate information that they needed by search engines. Clustering search engine results is an effective method to help people select information needed from the list of search engine results. The paper presents a clustering algorithm of no-word-segmentation for Chinese search engine results (CANWS). The algorithm firstly preprocesses the search engine results and then computes the similarities of the results based on the same sub-string. Lastly it clusters the results based on the similarity matrix. The paper also gives test and analysis of the algorithm performance by experiments.

关键词： search engine results clustering results similarity algorithm clustering algorithm

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Research on Student Model of Adaptive Learning System Based on Semantic Web

Research on Student Model of Adaptive Learning System Based ...

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2013 World Congress on Industrial Materials-Applications,Products,and Technologies(WCIM 2013)

作者： Jianqiong Xiao Experiment Center of China West Normal University

This paper came up with introducing four dimensions: learning mood, cognitive state, learning style and interest preference and so on for the semantic web, based on the analysis the present situation student models at home and abroad. Realized to classify learners and establish student models which used an improved similarity algorithm, and the student model applied to adaptive learning system, which not only could solve the lack semantic in adaptive learning system, and greatly improves the practicability, intelligent and personalized.

关键词： adaptive learning system semantic Web student model similarity algorithm

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The Development of Ontology-based Intelligent Retrieval algorithm and Prototype System of Mechanical Products

The Development of Ontology-based Intelligent Retrieval Algo...

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7th World Congress on Intelligent Control and Automation (WCICA 2008), vol.12

作者： Yanwei Zhao Bin Guan Jingling Zhang Yuankun Gui Jian Hu College of Mechanical Engineering Zhejiang University of Technology Hangzhou Zhejiang China

For the better and stronger information retrieval function, the sequence of search result queue and the correlation of query expression are the key problems that could be computed by similarity algorithm. A new method which is ontology-based weighted semantic tree similarity algorithm (OWSTS) is presented here. In this paper, the construction method of OWSTS and the implementation of similarity algorithm are introduced firstly. And an ontology-based information retrieval prototype system of mechanical products domain is developed secondly. Finally the relative accuracy of retrieval results by OWSTS and generally used cosine vector space based similarity algorithm (TF*IDF) are compared. The successful running of this system shows that OWSTS algorithm is feasible for information retrieval and the similarity algorithm makes the sequence of search result queue fit for users' semantic requirement.

关键词： Mechanical product Domain ontology Weighted semantic tree similarity algorithm Intelligent retrieval

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Research on Personalized Recommendation Based on Big Data Technology

Research on Personalized Recommendation Based on Big Data Te...

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作者： Jinhai Li Shichao Qi Longfeng Chen Hui Yan School of Computer Science and Technology Taizhou University

Aiming at the sparsity problem existing in the traditional collaborative filtering algorithm, this paper proposed an improved similarity computing method that integrated user rating behavior and item attributes. The sparse matrix is evaluated and predicted by the similarity calculation method, then the prediction rating was filled in the sparse matrix. At the same time, in the context of big data, the data scale was too large to affect the execution efficiency of the recommendation system. Hadoop platform was adopted to implement collaborative filtering recommendation algorithm based on the improved similarity model. Based on large-scale data segmentation, the distributed parallel processing was carried out. The proposed improved algorithm is verified by Movielens which was an internationally standard data set. The verification results show that the personalized recommendation system based on Hadoop platform and improved recommendation algorithm has better recommendation performance.

关键词： Big data Personalized recommendation similarity algorithm Data sparsity Distributed parallel processing

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基于语义的同义词识别算法研究

基于语义的同义词识别算法研究

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第二届全国学生计算语言学研讨会

作者：章成志章成敏王萍南京大学信息管理系中国药科大学图书馆南京工业职业技术学院工商管理系

1 引言随着海量信息的出现和不断增加,同义词控制显得更加重要,它是实现概念检索的一个途径,具有概念检索功能的网络信息检索工具可借助于一个同义词表对用户输入的关键词自动添加同义词,有助于提高查全率,但不降低查准率。对同义词识... 详细信息

1 引言随着海量信息的出现和不断增加,同义词控制显得更加重要,它是实现概念检索的一个途径,具有概念检索功能的网络信息检索工具可借助于一个同义词表对用户输入的关键词自动添加同义词,有助于提高查全率,但不降低查准率。对同义词识别的研究

关键词： Synonyms Recognition Synonyms Dictionary Semantic Dictionary similarity algorithm

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