Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (9): 215-220.doi: 10.11896/jsjkx.210700190

• Artificial Intelligence • Previous Articles     Next Articles

Ontology Alignment Method Based on Self-attention

WU Zi-yi, LI Shao-mei, JIANG Meng-han, ZHANG Jian-peng   

  1. National Digital Switching System Engineering &Technological R & D Center,Zhengzhou 450002,China
  • Received:2021-07-19 Revised:2022-02-28 Online:2022-09-15 Published:2022-09-09
  • About author:WU Zi-yi,born in 1998,master.Her main research interests include know-ledge graph and NLP.
    LI Shao-mei,born in 1982,Ph.D,asso-ciate professor,master supervisor.Her main research interests include know-ledge graph and NLP.
  • Supported by:
    Young Scientists Fund of the National Natural Science Foundation of China(62002384) and Zhengzhou Collaborative Innovation Major Project(162/32410218).

PDF (PC)

528

Abstract: With the development of knowledge graph in the field of artificial intelligence,there is an increasing demand to integrate knowledge graph from different sources to obtain a big knowledge graph with wider coverage.Ontology is the superstructure that can guide the construction of knowledge graph.To solve the problem of ontology alignment in knowledge graph fusion,this paper proposes an ontology alignment method based on self-attention model to combine multidimensional similarities.Firstly,two concepts from two ontologies are multi-dimensional measured by string-based,semantic-based and structure-based similarities.Then,self-attention model is used to combine above similarity calculations to judge whether the two concepts are similar or not and align them.Experiments on public datasets show that,compared with existing ontology alignment methods,the proposed method can obtain better alignment results by aggregating multi-dimensional similarity features.

Key words: Knowledge graph fusion, Ontology alignment, Similarity calculation, Self-attention model

CLC Number: 

  • TP391.1
[1]EUZENAT J,SHVAIKO P.Ontology Matching[M].Berlin:Springer-Verlag,2007:25-54.
[2]WANG S,KANG D Z,JIANG D Y.Survey of Ontology Mapping[J].Computer Science,2017,44(9):1-10.
[3]XU J,FANG A,HONG N.An Ontology Mapping MethodBased on Lexical Similarity Calculation[J].New Technology of Library and Information Service,2013,29(2):36-42.
[4]YAO X M,WANG F,LIN L F,et al.An Efficient Multi-policy Ontology Mapping Method[J].Chinese Science and Technology Papers,2013,8(7):642-647.
[5]YU J,XIONG Z H,OU Z H.Eliminating Redundant Ontology Relations Based on Hasse Diagram[J].Journal of the China Society for Scientific and Technical Information,2015,34(3):279-285.
[6]JIANG M,YU M G,WANG Z X.Multi-strategy AdaptiveLarge-scale Ontology Mapping Algorithm[J].Computer Engineering,2019,45(3):14-19.
[7]EUZENAT J,GUÉGAN P,VALTCHEVP.OLA in the OAEI2005 alignment contest[C]//Proceedings of the K-CAP 2005 Workshop on Integrating Ontologies.2005:61-71.
[8]NEZHADI A,SHADGAR B,OSAREH A.Ontology Alignment Using Machine LearningTechniques[J].International Journal of Computer Science & Information Technology,2011,12(3):139-150.
[9]ALBOUKAEY N,JOUKHADAR A.Ontology Matching as Regression Problem[J].Journal of Digital Information Management,2018,16(1):85-99.
[10]LEV B,SERGEY S.Applying of Machine Learning Techniques to Combine String-based,Language-based and Structure-based Similarity Measures for Ontology Matching[C]//Selected Papers of the XXI International Conference on Data Analytics and Management in Data Intensive Domains.2019:129-147.
[11]SENGODAN M,SAMUKUTTY A.Explicit Link DiscoveryScheme Optimized with Ontology Mapping using Improved Machine Learning Approach[J].Studies in Informatics and Control,2021,30(1):189-201.
[12]SABOU M,THIÉBLIN E,HAEMMERLÉ O,et al.Survey on complex ontology matching[J].Semantic Web,2020,11(4):32-62.
[13]WANG R J.Research on Ontology Mapping Methods[D].Changchun:Jilin University,2012.
[14]LOU W,WANG H,JU Y.An ontology fusion method based on binary similarity calculation[J].Journal of the China Society for Scientific and Technical Information,2019,38(6):622-631.
[15]SUN X.Research on Ontology Alignment Based on Word Embedding[D].Harbin:Harbin Institute of Technology,2020.
[16]CHEN E J,JIANG E B.Review of Studies on Text Similarity Measures[J].Data Analysis and Knowledge Discovery,2017,1(6):1-11.
[17]LIN H L,WANG Y Z,JIA Y T,et al.Network Big Data Oriented Knowledge Fusion Methods:A Survey[J].Chinese Journal of Computers,2017,40(1):1-27.
[18]KANG S Z,JI L X,ZHANG J P.Ontology Alignment Method Based on Word Embedding and Conceptual Context Information[J].Journal of Information Engineering University,2020,21(5):607-613.
[19]SAEDI C,BRANCOA,RODRIGUES J,et al.Wordnet embeddings[C]//Proceedings of the Third Workshop on Representation Learning for NLP.2018:122-131.
[20]JANG B,KIM I,KIM J W.Word2vec convolutional neural networks for classification of news articles and tweets[J].PloS One,2019,14(8):178-189.
[21]LE Q V,MIKOLOV T.Distributed Representations of Sen-tences and Documents[C]//International Conference on Machine Learning.2014:1188-1196.
[22]VASWANI A,SHAZEER N,PARMAR N,et al.Attention isall you need[C]//Advances in Neural Information Processing Systems.2017:5998-6008.
[23]LIN T,GOYAL P,GIRSHICK R,et al.Dollar Piotr.Focal Loss for Dense Object Detection[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,42(2):178-185.
[24]DAVID J,GUILLET F,BRIAND H.Association Rule Ontology Matching Approach[J].In:International Journal on Semantic Web and information systems,2007,3(2):27-49.
[25]ECKERT K,MEILICKE C,STUCKENSCHMIDT H.Impro-ving ontology matching using meta-level learning[C]//Euro-pean Semantic Web Conference.Berlin:Springer,2009:158-172.
[1] WANG Yi, LI Zheng-hao, CHEN Xing. Recommendation of Android Application Services via User Scenarios [J]. Computer Science, 2022, 49(6A): 267-271.
[2] CHEN Ying-ren, GUO Ying-nan, GUO Xiang, NI Yi-tao, CHEN Xing. Web Page Wrapper Adaptation Based on Feature Similarity Calculation [J]. Computer Science, 2021, 48(11A): 218-224.
[3] ZHONG Ya,GUO Yuan-bo,LIU Chun-hui,LI Tao. User Attributes Profiling Method and Application in Insider Threat Detection [J]. Computer Science, 2020, 47(3): 292-297.
[4] XU Fei-xiang,YE Xia,LI Lin-lin,CAO Jun-bo,WANG Xin. Comprehensive Calculation of Semantic Similarity of Ontology Concept Based on SA-BP Algorithm [J]. Computer Science, 2020, 47(1): 199-204.
[5] WU Yi-fan, CUI Yan-peng, HU Jian-wei. Alert Processing Method Based on Hierarchical Clustering [J]. Computer Science, 2019, 46(4): 203-209.
[6] LU Xian-hua, WANG Hong-jun. Design of Distributed News Clustering System Based on Big Data Computing Framework [J]. Computer Science, 2019, 46(11A): 220-223.
[7] YU Shan-shan, SU Jin-dian and YI Fa-ling. Descriptions for Ontologies Based on Category Theory [J]. Computer Science, 2016, 43(5): 42-46.
[8] WEN Jun-hao and SHU Shan. Improved Collaborative Filtering Recommendation Algorithm of Similarity Measure [J]. Computer Science, 2014, 41(5): 68-71.
[9] . Things Networking Cloud Storage Data Bad Information Detection Based on Boundary-incremental SVM Algorithm [J]. Computer Science, 2013, 40(2): 95-97.
[10] . Formalizing Geo-ontology Alignment and Integration Based on Category Theory [J]. Computer Science, 2012, 39(7): 242-244.
[11] . Personalized Recommendation Model Based on the Dynamic and Mixed QoS of Semantic Web Service [J]. Computer Science, 2012, 39(4): 149-153.
[12] ZHANG Qing-jun XU De-zhi CHEN Jian-er （College of Information Science and Engineering, Central South University,Changsha 410083 ,China）. [J]. Computer Science, 2009, 36(5): 229-233.
[13] YU Juan DANG Yan-zhong （Institute of System Engineering, Dalian University of Technology, Dalian 116023, China）. [J]. Computer Science, 2008, 35(7): 9-13.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.