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29th International Conference on Computer Communications and Networks (ICCCN)

作者： Li, Ruike Tan, Shichong Wu, Chensi Cao, Xudong He, Haitao Wang, Wenjie Xidian Univ Sch Cyber Engn Xian Peoples R China Univ Chinese Acad Sci Natl Comp Network Intrus Protect Ctr Beijing Peoples R China Yanshan Univ Coll Informat Sci & Engn Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781728166070

Security vulnerability database research is an essential part of information security research. With the sharp increase in the number of vulnerabilities in recent years, it has become increasingly important to collect and organize information about existing vulnerability databases. However, there is heterogeneity and redundancy of data between the databases, which makes it challenging to share vulnerability information. In response to the above problems, a comprehensive security vulnerability collection model is proposed. A total of 1.005 million pieces of vulnerability data are collected and analyzed in 11 mainstream vulnerability databases. By introducing the idea of the collection of automation, problems such as the untimely update of vulnerability database information and the low efficiency of vulnerability collection, are solved effectively. The structural framework and functional modules of the automatic vulnerability collection system are introduced, and the specific implementation of the system is given. Based on the text processing technology, the rules of deduplication (95.6% accuracy) and the intelligent framework for vulnerability database (IFVD) are proposed and implemented. Finally, Experiments show the feasibility of the scheme.

关键词： vulnerability data similarity algorithm field fusion framework

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Construction of MeSH-like Obstetric Knowledge Graph 10

Construction of MeSH-like Obstetric Knowledge Graph

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10th International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

作者： Zhang, Kunli Li, Kaixiang Ma, Hongchao Yue, Donghui Zhuang, Lei Zhengzhou Univ Sch Informat Engn Zhengzhou Henan Peoples R China Zhengzhou Univ Affiliated Hosp 1 Zhengzhou Henan Peoples R China

ISBN: (数字)9781728109749

ISBN: (纸本)9781728109749

Obstetric Knowledge Graph describes the obstetric diseases and the body parts, drugs, etc. as well as the relations between them, which is an important knowledge base for intelligent auxiliary diagnosis. In this paper, the hierarchical structure of Medical Subject Headings(MeSH) is taken as the ontology prototype of the Knowledge Graph. According to the naming criterion of Chinese obstetric diseases and the practical application of the disease diagnosis in obstetric electronic medical records. And the ontology structure of obstetric diseases is extended. Moreover, the possible relation categories between obstetric entities and knowledge description system are defined to form the schema layer of Obstetric Knowledge Graph. The obstetric disease attributes of heterogeneous data are derived from medical specifications, classic textbooks, and medical online website by using rules-based and wrapper methods. And then they are fused by the Simhash-TF-IDF algorithm. The relations between entities in the knowledge graph are extracted by combining Bootstrapping and SVM algorithms. Then the Obstetric Knowledge Graph data layer is completed. The schema layer and data layer are automatically imported into Protege to visualize the Obstetric Knowledge graph. The constructed Obstetric Knowledge Graph contains 625 entities, 2456 attributes and 1407 relations, which covers the most diseases in obstetrics and related entities.

关键词： Knowledge Graph Obstetrics Ontology Information extraction 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

作者： Zhao, Yanwei Guan, Bin Zhang, Jingling Gui, Yuankun Hu, Han Zhejiang Univ Technol Coll Mech Engn Hangzhou 310032 Zhejiang Peoples R China

ISBN: (纸本)9781424421138

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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Exploring Information Systems (IS) curricula: a semantic analysis approach

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INFORMATION DISCOVERY AND DELIVERY 2024年第3期52卷 354-364页

作者： Shi, Hui Hwang, Drew Chong, Dazhi Yan, Gongjun Calif State Polytech Univ Pomona Dept Comp Informat Syst Pomona CA 91768 USA Calif Lutheran Univ Sch Management Thousand Oaks CA USA Univ Southern Indiana Dept Management & Informat Sci Evansville IN USA

PurposeToday's in-demand skills may not be needed tomorrow. As companies are adopting a new group of technologies, they are in huge need of information technology (IT) professionals who can fill various IT positions with a mixture of technical and problem-solving skills. This study aims to adopt a sematic analysis approach to explore how the US Information Systems (IS) programs meet the challenges of emerging IT ***/methodology/approachThis study considers the application of a hybrid semantic analysis approach to the analysis of IS higher education programs in the USA. It proposes a semantic analysis framework and a semantic analysis algorithm to analyze and evaluate the context of the IS programs. To be more specific, the study uses digital transformation as a case study to examine the readiness of the IS programs in the USA to meet the challenges of digital transformation. First, this study developed a knowledge pool of 15 principles and 98 keywords from an extensive literature review on digital transformation. Second, this study collects 4,093 IS courses from 315 IS programs in the USA and 493,216 scientific publication records from the Web of Science Core *** the knowledge pool and two collected data sets, the semantic analysis algorithm was implemented to compute a semantic similarity score (DxScore) between an IS course's context and digital transformation. To present the credibility of the research results of this paper, the state ranking using the similarity scores and the state employment ranking were compared. The research results can be used by IS educators in the future in the process of updating the IS curricula. Regarding IT professionals in the industry, the results can provide insights into the training of their current/future ***/valueThis study explores the status of the IS programs in the USA by proposing a semantic analysis framework, using digital transformation as a case study to illustrate the a

关键词： IS curricula Semantic analysis similarity algorithm Knowledge pool Keyword co-occurrence Digital transformation

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Finger Disability Recognition Based on Holistically-Nested Edge Detection 15th

Finger Disability Recognition Based on Holistically-Nested E...

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15th International Conference on Intelligent Robotics and Applications (ICIRA ) - Smart Robotics for Society

作者： Bai, Dianchun Zheng, Xuesong Liu, Tie Li, Kairu Yang, Junyou Shenyang Univ Technol Shenyang Peoples R China

ISBN: (纸本)9783031138447;9783031138430

In order to relieve the medical pressure, when patients with finger disability see a doctor, the degree of finger disability can be identified and judged by the equipment first, and then the doctor carries out the next step of diagnosis and treatment. Aiming at the problem that the traditional recognition algorithm is not ideal, this paper proposes a finger disability recognition algorithm based on Holistically-nested edge detection algorithm. On the basis of extracting the edge of hand image with Holistically-nested edge detection algorithm, the similarity judgment is made between the experimental object's hand edge detection image and the standard hand edge detection image. The degree of finger joint integrity was analyzed by different similarity judgment, and then the degree of finger disability was judged. In order to verify the effectiveness of the method, 50 people's hand images were collected to establish a sample database of hand images, and a total of 600 simulated severed finger images were tested. The accuracy of finger disability recognition was 96.6%. This algorithm can effectively identify the degree of finger disability and improve the medical efficiency.

关键词： Finger recognition Edge detection similarity algorithm Image recognition

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On-Line Text Mining and Recommendation based on Ontology and Implied Sentiment Inclination 17

On-Line Text Mining and Recommendation based on Ontology and...

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17th IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATIONS TECHNOLOGY (ICACT)

作者： Yang, Hui Wang, Zhe Xu, Hao Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Coll Elect Sci & Engn Changchun 130012 Peoples R China

ISBN: (纸本)9788996865056

Most of the exist Web search engines utilize matching the query keywords to pieces of information approach to identify of the data satisfying user's request. These methods are not only inefficient, but also wasted a lot of user's time to find a satisfactory results. In order to improve the problem above, we presented a different approach to identify user's request that attracts more interest is called a ontology-based and implied sentiment search. Ontology is a tree structure which represent specifications of concepts and relations among them. Ontology play a central role in semantic web applications by providing a shared knowledge about the objects in real world. This paper proposes a method for determining semantic similarity between concepts and implied sentiment defined in ontology. Unlike method exist that use ontological definition of concepts for similarity assessment, the presented approach also focuses on the relations between concepts and their implied sentiment inclination. Our method is able to determine similarity not only at the definition level, but also is able to evaluate similarity of implied sentiment of information that are instances of concepts. In addition, the method allows for context-aware similarity assessment. Experimental comparison of our on-line text mining approach against other techniques known in the literature shows satisfying results.

关键词： Sentiment Inclination Analysis Text Mining Ontology similarity algorithm recommendation method

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Research on matching method for case retrieval process in CBR based on FCM 13th

Research on matching method for case retrieval process in CB...

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13th Global Congress on Manufacturing and Management (GCMM)

作者： Zhao Yamin Zhang Mengmeng Guo Xiaomin Zhou Zhiwei Zhang Jianhua Zhengzhou Univ Dept Engn Management Zhengzhou Peoples R China

Era of knowledge economy, how to effectively mining, the use of knowledge is the enterprise growing concern. CBR system from the field of artificial intelligence is a self-learning system to manage tacit knowledge (case). Case retrieval link is the core link, the advantages and disadvantages of search methods directly affect the efficiency of case retrieval and case matching accuracy. Therefore, this paper proposes a new case matching process: when the size of the case database is small, it searches based on the case similarity algorithm;when the case database is large, it searches based on the FCM secondary retrieval model. And illustrates the fastness and efficiency of FCM in matching large-scale case database. (C) 2017 The Authors. Published by Elsevier Lid.

关键词： CBR case matching similarity algorithm FCM

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Reconstructing Regular Shredded Documents by similarity Measure

Reconstructing Regular Shredded Documents by Similarity Meas...

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2014 2nd International Conference on Soft Computing in Information Communication Technology(SCICT 2014)

作者： Cheng Le Nanjie Deng Xiao Jin Beijing University of Posts and Telecommunications BUPT

This paper describes a method to the problem of reconstructing regular shredded documents by similarity measure. Regular shredded document can be quantized as gray-level matrix or two-value matrix. So we can match the gray value of the edge of the shredded document, which is indicated as similarity value. We calculate the similarity value by using improved minimum-error method, a kind of similarity measure method. The two shredded owning the biggest similarity value is probable to be the neighboring ones. So we can reconstruct these regular shredded documents through this method until it is recovered.

关键词： reconstruct shredding minimum-error method similarity algorithm similarity measure

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Evaluation of string comparators for record linkage in Chinese environment

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INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 2022年第6期20卷 2250023-2250023页

作者： Guo, Heng Li, Yalin Liu, Ying Li, Weifu Li, Xinran Huazhong Agr Univ Coll Sci Dept Math & Stat Wuhan 430070 Peoples R China

In Chinese record linkage, the similarity measurement of short text fields such as identifying information has an important influence on the effect of linkage. In this paper, we compared the performance of six different string comparators for Chinese record linkage, including Hamming, Levenshtein, Jaro, Overlap Coefficient, Cosine and Ratcliff-Obershelp similarity. At the same time, the expectation-maximization algorithm was used to perform the probabilistic record linkage. The results showed that compared with other string comparators, Jaro similarity not only gets higher precision and recall, but also has the least computational time. All in all, this comparator can be used if we focus on string spelling and pronunciation without considering semantic similarity.

关键词： Record linkage Chinese characters similarity algorithm Sound-Shape Code Fellegi-Sunter model

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Research on Matching Method for Case Retrieval Process in CBR Based on FCM

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Procedia Engineering 2017年 174卷 267-274页

作者： Zhao Yamin Zhang Mengmeng Guo Xiaomin Zhou Zhiwei Zhang Jianhua Management Engineering Department ZhengzhouUniversity Zhengzhou China

Era of knowledge economy, how to effectively mining, the use of knowledge is the enterprise growing concern. CBR system from the field of artificial intelligence is a self-learning system to manage tacit knowledge (case). Case retrieval link is the core link, the advantages and disadvantages of search methods directly affect the efficiency of case retrieval and case matching accuracy. Therefore, this paper proposes a new case matching process: when the size of the case database is small, it searches based on the case similarity algorithm; when the case database is large, it searches based on the FCM secondary retrieval model. And illustrates the fastness and efficiency of FCM in matching large-scale case database.

关键词： CBR case matching similarity algorithm FCM

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