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Domain-Specific Formal Ontology of Archaeology and Its Application in knowledge acquisition and Analysis

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Journal of Computer Science & Technology 2004年第3期19卷 290-301页

作者： Chun-XiaZhang Cun-GenCao FangGu Jin-XinSi KeyLaboratoryofIntelligentInformationProcessing InstituteofComputingTechnologyTheChineseAcademyofSciencesBeijing100080P.R.China／／GraduateSchooloftheChineseAcademyofSciencesBeijing100039P.R.China KeyLaboratoryofIntelligentInformationProcessing Instituteo／ComputingTechnologyTheChineseAcademyofSciencesBeijing100080P.R.China

Inherent heterogeneity and distribution of knowledge strongly prevent knowledge from sharing and reusing among different agents and software entities, and a formal ontology has been viewed as a promising means to tackle this problem. In this paper, a domain-specific formal ontology of archaeology is presented. The ontology mainly consists of three parts: archaeological categories, their relationships and axioms. The ontology not only captures the semantics of archaeological knowledge, but also provides archaeology with an explicit and formal specification of a shared conceptualization, thus making archaeological knowledge shareable and reusable across humans and machines in a structured fashion. Further, we propose a method to verify ontology. correctness based on the individuals of categories. As applications of the ontology,we have developed an ontology-driven approach to knowledge acquisition from archaeological text and a question answering system for archaeological knowledge.

关键词： domain-specific ontology archaeology category ontology correctness knowledge acquisition question-answering system

Toward Effective knowledge acquisition with First—Order Logic Induction

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Journal of Computer Science & Technology 2002年第5期17卷 565-577页

作者：张晓龙 Masyuki Numao IT Solution Delivery AXA Life Insurance Company Tokyo 194-0022 Japan Department of Computer Science Tokyo Institute of Technology Tokyo 152-8552 Japan

knowledge acquisition with machine learning techniques is a fundamental re-quirement for knowledge discovery from databases and data mining systems. Two techniquesin particular - inductive learning and theory revision - have been used toward this end. Amethod that combines both approaches to effectively acquire theories (regularity) from a setof training examples is presented. Inductive learning is used to acquire new regularity fromthe training examples; and theory revision is used to improve an initial theory. In addition, atheory preference criterion that is a combination of the MDL-based heuristic and the Laplaceestimate has been successfully employed in the selection of the promising theory. The resultingalgorithm developed by integrating inductive learning and theory revision and using the criterionhas the ability to deal with complex problems, obtaining useful theories in terms of its predictiveaccuracy.

关键词： knowledge acquisition inductive logic programming theory revision the MDL principle the Laplace estimate noisy data

A Survey of Commonsense knowledge acquisition

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Journal of Computer Science & Technology 2013年第4期28卷 689-719页

作者：臧良俊曹聪曹亚男吴昱明曹存根 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences University of the Chinese Academy of Sciences The Second Lab Institute of Information Engineering Chinese Academy of Sciences

Collecting massive commonsense knowledge （CSK） for commonsense reasoning has been a long time standing challenge within artificial intelligence research. Numerous methods and systems for acquiring CSK have been developed to overcome the knowledge acquisition bottleneck. Although some specific commonsense reasoning tasks have been presented to allow researchers to measure and compare the performance of their CSK systems, we compare them at a higher level from the following aspects： CSK acquisition task （what CSK is acquired from where）, technique used （how can CSK be acquired）, and CSK evaluation methods （how to evaluate the acquired CSK）. In this survey, we first present a categorization of CSK acquisition systems and the great challenges in the field. Then, we review and compare the CSK acquisition systems in detail. Finally, we conclude the current progress in this field and explore some promising future research issues.

关键词： commonsense knowledge knowledge acquisition knowledge representation and reasoning

Intelligent Multilevel knowledge acquisition System for Product Design and Its Implementation

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High Technology Letters 2001年第1期7卷 37-41页

作者：钟佩思 Xu Wensheng Zeng Qingliang Xiong Guangleng GAO Guoan National CIMS Engineering Research Center Tsinghua University Advanced Manuf. Tech. Center Harbin Institute of Technology

The characteristics of design process, design object and domain knowledge of complex product are analyzed. A kind of knowledge representation schema based on integrated generalized rule is stated. An AND-OR tree based model of concept for domain knowledge is set up. The strategy of multilevel domain knowledge acquisition based on the model is presented. The intelligent multilevel knowledge acquisition system (IMKAS) for product design is developed, and it is applied in the intelligent decision support system of concept design of complex product.

关键词： Product design Domain knowledge knowledge representation Generalized rule knowledge acquisition

Product Evaluation knowledge acquisition Based on Rough Sets

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Computer Aided Drafting,Design and Manufacturing 2006年第2期16卷 83-87页

作者： XU Xiao-hui TONG Bing-shu Department of Precision Instruments and Mechanoiogy Tsinghua University Beijing 100084 China

The method and steps of acquiring evaluation rules based on the knowledge reduction theory of rough sets is discussed, and the distilling process and approach for the evaluation rules of mechanical product structure design is described by using hydraulic torque converter as an example. Practice shows that this approach to a certain extent simplifies the knowledge base structure and reasoning process in comparison with the case-based reasoning method in the aspect of setting up evaluation rule base and carrying out reasoning to realize the mechanical product evaluation.

关键词： product design evaluation knowledge acquisition rough set knowledge reduction

Multi-Condition knowledge acquisition for Byproduct Energy Scheduling based on Hierarchical Granular Contrastive Network

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Multi-Condition Knowledge Acquisition for Byproduct Energy S...

第32届中国过程控制会议(CPCC2021)

作者： Tianyu Wang Jun Zhao Wei Wang Tianxin Wang School of Control Science and Engineering Dalian University of Technology

A real-time effective scheduling for byproduct energy systems is important for achieving energy saving and consumption reduction.Considering that the energy system is characterized by multiple operating conditions,a knowledge acquisition and representation algorithm based on hierarchical granular contrastive network is proposed.In view of the capabilities of deep contrast learning for processing semantic information,a series of information granules are first defined and described to establish a semantic representation of the energy data.To extract multi-condition scheduling knowledge,a long and short-term memory(LSTM) network is used to learn the time-varying characteristics of granular variables.On top of this,a knowledge representation network based on granular contrastive learning is established,which takes advantage of the expert knowledge to partition the contrastive samples.For digging out deep-level hidden information,a hierarchical contrastive network model is further proposed by employing a closed-loop feedback mechanism.The practical operation data coming from the blast furnace gas system of a domestic steel plant are utilized to perform our experiments.The results show that the multi-condition knowledge representation obtained by the proposed method would help improve the performance of system modeling and realize human-level scheduling performance.

关键词： Byproduct energy system multi-condition knowledge acquisition information granularity contrastive learning

Study of Testability knowledge acquisition Based on Graph Theory Model

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Study of Testability Knowledge Acquisition Based on Graph Th...

2006年国际电子、工程及科学领域的分布式计算和应用学...

作者： GuangYao Lian KaoLi Huang JianHui Chen FengQi Gao Department 4 Ordnance Engineering College Shijiazhuang Hebei 050003 China

＜正＞It puts forward a testability knowledge acquisition method based on graph theory to solve the testability knowledge acquisition for complex electronic products. Function-structure models are built from using graph theory principle.From calculating the reachable matrix of system,we can get the significant values of nodes.The node that has large significant value is used to divide up the reachable matrix,and dividing up the matrix can get the best fault isolation nodes.Then,we can calculate the amount of information of every node to ascertain the best fault detect nodes.Finally,the best fault diagnosis policy of system can be got.The technology has important meaning in solving the problem of testability-knowledge acquisition in the moment of testability preliminary design.It can also improve intelligent level of testability design and analysis.

关键词： knowledge acquisition knowledge Utilization Graph Theory Model Testability design Fault Diagnosis

The Research of IETM knowledge acquisition Based on Semantic Wiki

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The Research of IETM Knowledge Acquisition Based on Semantic...

IEEEBEIJINGSECTION(跨国电气电子...

作者： Xue Jianwu School of Management Northwestern Polytechnical University Xi’an China Chen Na Gou Miao School of Management Northwestern Polytechnical University Xi’an China

＜正＞The acquisition about implicit knowledge of experts,technicists’ experience,in addition to the structural knowledge inquired by intelligent IETM are the bottleneck in all IETM projects,this problem is paid close attention to by academic circles.The development and application of Semantic Wiki provides a new solution for it.The paper presents an IETM knowledge acquisition model at the core of Semantic Wiki,and discusses the process of the knowledge acquisition,laying the foundation for the IETM projects.

关键词： Semantic Wiki Intelligent IETM RDF knowledge acquisition

Application of Rapid knowledge acquisition Method in Intelligent Diagnosis Instrument

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Application of Rapid Knowledge Acquisition Method in Intelli...

第一届国际测量仪器与测试自动化学术会议

作者： Xu Xiaoli Zuo Yunbo Wen Houzhen Wang Xibin Shi Yongchao ( Beijing Institute of Machinery Beijing 100085 China) ( School of Mechanical and Vehicular Engineering Beijing Institute of Technology Beijing 100081 China)

＜正＞The knowledge acquisition has become a bottleneck problem of using artificial intelligence to build the intelligent diagnosis instrument. Rough set theory has attracted great attention because of its high performance on knowledge acquisition. The decision table based on the field data of the classical faults of the rotating machinery is created in the paper. Discernibility matrix to reduce the attribute and attribute values of the decision table is used. Finally, the rules are got and the knowledge of the intelligent diagnosis instrument is acquired rapidly.

关键词： knowledge acquisition rotating machinery fault prediction rough set discernibility matrix.