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Integrated semantic similarity Model Based on Ontology

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Wuhan University Journal of Natural Sciences 2004年第5期9卷 601-605页

作者： LIUYa-Jun ZHAOYun DepartmentofComputerScienceandEngineering.SoutheastUniversity Nanjing210096.JiangsuChina

To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowledge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is very satisfied. Key words intelligent question answering system - ontology - semantic similarity - geometric distance - information content CLC number TP39 Foundation item: Supported by the important science and technology item of China of “The 10th Five-year Plan” (2001BA101A05-04)Biography: LIU Ya-jun (1953-), female, Associate professor, research direction: software engineering, information processing, data-base application.

关键词： intelligent question answering system ontology semantic similarity geometric distance information content

SERVICE COMMUNITY CONSTRUCTION METHOD OF INTERNET OF THINGS BASED ON semantic similarity

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Journal of Electronics(China) 2013年第1期30卷 49-56页

作者： Wang Yang Zhang Linjing Huang Yakun Zhao Baohua Zhao Chuanxin Department of Computer Science Anhui Normal University Department of Computer Science and Technology University of Science and Technology of China

Internet of Things (IoT) as an important and ubiquitous service paradigm is one of the most important issues in IoT applications to provide terminal users with effective and efficient services based on service community. This paper presents a semantic-based similarity algorithm to build the IoT service community. Firstly, the algorithm reflects that the nodes of IoT contain a wealth of semantic information and makes them to build into the concept tree. Then tap the similarity of the semantic information based on the concept tree. Finally, we achieve the optimization of the service community through greedy algorithm and control the size of the service community by adjusting the threshold. Simulation results show the effectiveness and feasibility of this algorithm.

关键词： Internet of Things (IoT) Service community semantic similarity Concept tree

Task-oriented web service discovery algorithm using semantic similarity for adaptive service composition

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Journal of Southeast University(English Edition) 2009年第4期25卷 468-472页

作者：文俊浩江卓涂丽云何盼重庆大学计算机学院重庆400030 重庆大学软件工程学院重庆400030

In order to achieve adaptive and efficient service composition, a task-oriented algorithm for discovering services is proposed. The traditional process of service composition is divided into semantic discovery and functional matching and makes tasks be operation objects. semantic similarity is used to discover services matching a specific task and then generate a corresponding task-oriented web service composition （TWC） graph. Moreover, an algorithm for the new service is designed to update the TWC. The approach is applied to the composition model, in which the TWC is searched to obtain an optimal path and the final service composition is output. Also, the model can implement realtime updating with changing environments. Experimental results demonstrate the feasibility and effectiveness of the algorithm and indicate that the maximum searching radius can be set to 2 to achieve an equilibrium point of quality and quantity.

关键词： web service service composition service discovery ontology semantic similarity

Integrated semantic similarity Model Based on Ontology

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Integrated Semantic Similarity Model Based on Ontology

Improved semantic similarity Algorithm Based on Ontology

The First Conference on Web Information System and Applications

作者： LIU Ya-Jun ZHAO YunDepartment of Computer Science and Engineering. Southeast University Nanjing 210096 Jiangsu China

＜正＞ To solve the problem of the inadequacy of semantic processing in the intelligent question answering system, an integrated semantic similarity model which calculates the semantic similarity using the geometric distance and information content is presented in this paper. With the help of interrelationship between concepts, the information content of concepts and the strength of the edges in the ontology network, we can calculate the semantic similarity between two concepts and provide information for the further calculation of the semantic similarity between user’s question and answers in knowlegdge base. The results of the experiments on the prototype have shown that the semantic problem in natural language processing can also be solved with the help of the knowledge and the abundant semantic information in ontology. More than 90% accuracy with less than 50 ms average searching time in the intelligent question answering prototype system based on ontology has been reached. The result is ver-y satisfied.

关键词： intelligent question answering system ontology semantic similarity geometric distance information content

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Improved Semantic Similarity Algorithm Based on Ontology

Words semantic orientation classification based on HowNet

The 2011 International Conference on Mechanical Materials and Manufacturing Engineering(ICMMME 2011)

作者： Junying Wei Peisi Zhong Chunfen Guo College of Mechanical and Electronic Engineering Shandong University of Science and Technology

The measuring of semantic similarity is the key technique in information *** on the common semantic similarity algorithm between concepts,this paper makes use of semantic weighted distance and introduces such factors as node density,concept attribute and concept information content,and presents an improved semantic similarity algorithm to make the measuring semantic similarity more *** experimental calculation and analysis,the semantic similarity obtained from the improved algorithm can describe more accurately the similar relation between ontology concepts,and correspond to a higher degree with human subjective judgment.

关键词： ontology semantic distance semantic similarity

来源： cnki会议评论

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The Journal of China Universities of Posts and Telecommunications 2009年第1期16卷 106-110页

作者： LI Dun MA Yong-tao GUO Jian-li School of haformation Engineering Zhengzhou University Zhengzhou 450001 China School of Mechanical Engineering Zhengzhou University Zhengzhou 450001 China International College for Chinese Studies Nanjing Normal University Nanjing 210097 China

Based on the text orientation classification, a new measurement approach to semantic orientation of words was proposed. According to the integrated and detailed definition of words in HowNet, seed sets including the words with intense orientations were built up. The orientation similarity between the seed words and the given word was then calculated using the sentiment weight priority to recognize the semantic orientation of common words. Finally, the words＇ semantic orientation and the context were combined to recognize the given words＇ orientation. The experiments show that the measurement approach achieves better results for common words＇ orientation classification and contributes particularly to the text orientation classification of large granularities.

关键词： text classification semantic orientation semantic similarity orientation weight priority HowNet

SemTrust: A semantic Reputation System in P2P-Based semantic Web

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Wuhan University Journal of Natural Sciences 2006年第5期11卷 1137-1140页

作者： WANG Wei ZENG Guosun YUAN Lulai Department of Computer Science and Technology Tongii University Shanghai 201804 China Tongji Branch National Engineering and TechnologyCenter of High Performance Computer Shanghai 201804China

A reputation mechanism is introduced in P2P- based semantic Web to solve the problem of lacking trust. It enables semantic Web to utilize reputation information based on semantic similarity of peers in the network. This approach is evaluated in a simulation of a content sharing system and the experiments show that the system with reputation mechanism outperforms the system without it.

关键词： semantic Web reputation system semantic similarity trustworthiness

Unsupervised WSD by Finding the Predominant Sense Using Context as a Dynamic Thesaurus

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Journal of Computer Science & Technology 2010年第5期25卷 1030-1039页

作者： Javier Tejada-Carcamo Hiram Calvo Alexander Gelbukh Kazuo Hara San Pablo Catholic University ArequipaPeru Center for Computing Research National Polytechnic InstituteMexico City07738Mexico Nara Institute of Science and Technology TakayamaIkomaNara 630-0192Japan

We present and analyze an unsupervised method for Word Sense Disambiguation（WSD）.Our work is based on the method presented by McCarthy et *** 2004 for finding the predominant sense of each word in the entire *** maximization algorithm allows weighted terms（similar words） from a distributional thesaurus to accumulate a score for each ambiguous word sense,i.e.,the sense with the highest score is chosen based on votes from a weighted list of terms related to the ambiguous *** list is obtained using the distributional similarity method proposed by Lin Dekang to obtain a *** the method of McCarthy et al.,every occurrence of the ambiguous word uses the same thesaurus,regardless of the context where the ambiguous word *** method accounts for the context of a word when determining the sense of an ambiguous word by building the list of distributed similar words based on the syntactic context of the ambiguous *** obtain a top precision of 77.54%of accuracy versus 67.10%of the original method tested on *** also analyze the effect of the number of weighted terms in the tasks of finding the Most Precuent Sense（MFS） and WSD,and experiment with several corpora for building the Word Space Model.

关键词： word sense disambiguation word space model semantic similarity text corpus thesaurus

Bridging Real World semantics to Model World semantics for Taxonomy Based Knowledge Representation System

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Journal of Computer Science & Technology 2005年第3期20卷 296-308页

作者： Ju-HumKwon Chee-YangSong Chang-JooMoon Doo-KwonBaik DepartmentofComputerScienceandEngineering SoftwareSystemLaboratoryKoreaUniversity15-kaAnam-dongSungbuk-kuSeoul136-701Korea DepartmentofComputerScience KonkukUniversity322Danwol-dongChungju-siChungcheongbuk-do380-701Korea

As a mean to map ontology concepts, a similarity technique is *** a context dependent concept mapping is tackled, which needs contextual information fromknowledge taxonomy. Context-based semantic similarity differs from the real world similarity in thatit requires contextual information to calculate similarity. The notion of semantic coupling isintroduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degreeof semantic cohesiveness for a group of concepts toward a given context. In order to calculate thesemantic coupling effectively, the edge counting method is revisited for measuring basic semanticsimilarity by considering the weighting attributes from where they affect an edge''s strength. Theattributes of scaling depth effect, semantic relation type, and virtual connection for the edgecounting are considered. Furthermore, how the proposed edge counting method could be well adaptedfor calculating context-based similarity is showed. Thorough experimental results are provided forboth edge counting and context-based similarity. The results of proposed edge counting wereencouraging compared with other combined approaches, and the context-based similarity also showedunderstandable results. The novel contributions of this paper come from two aspects. First, thesimilarity is increased to the viable level for edge counting. Second, a mechanism is provided toderive a context-based similarity in taxonomy-based system, which has emerged as a hot issue in theliterature such as semantic Web, MDR, and other ontology-mapping environments.

关键词： semantic similarity context-based similarity edge counting semanticcoupling weighting attributes WordNet