文字与计算 |
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基于多源异构数据的甲骨学知识图谱构建方法研究 |
熊晶1,2, 焦清局1,2, 刘运通1 |
1.安阳师范学院 计算机与信息工程学院,河南 安阳 455000 2.甲骨文信息处理教育部重点实验室,河南 安阳 455000 |
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Oracle bone studies knowledge graph construction based on multi-source heterogeneous data |
XIONG Jing1,2, JIAO Qingju1,2, LIU Yuntong1 |
1.School of Computer & Information Engineering, Anyang Normal University, Anyang 455000, Henan Province, China 2.Key Laboratory of Oracle Bone Inscriptions Information Processing, Ministry of Education, Anyang 455000, Henan Province, China |
1 宋镇豪. 岁末年初对甲骨学的思考和期待[EB/OL]. [2019-03-20]. http://cass.cssn.cn/xuebuweiyuan/201812/t20181228_4802379.html. SONGZ H. The Thinking and Expectations of Oracle Bone Inscriptions at the End of the Year[EB/OL]. [2019-03-20]. http://cass.cssn.cn/xuebuweiyuan/201812/t20181228_4802379.html. 2 熊晶, 钟珞, 王爱民. 甲骨文知识图谱构建中的实体关系发现研究[J]. 计算机工程与科学, 2015,37(11):2188-2194. XIONGJ , ZHONGL , WANGA M. Research on entity relation discovery for oracle bone inscriptions knowledge mapping construction[J]. Computer Engineering&Science, 2015,37 (11) :2188-2194. 3 马如森. 殷墟甲骨学-带你走进甲骨文的世界[M]. 上海: 上海大学出版社, 2007. MAR S. Yin ruins of Oracle Bone Studies-Take you into the world of Oracle Bone Inscriptions [M]. Shanghai: Shanghai University Press, 2007. 4 陈悦, 刘则渊. 悄然兴起的科学知识图谱[J]. 科学学研究, 2005,23(2):149-154.DOI:10.16192/j.cnki.1003-2053.2005.02.002 CHENY, LIUZ Y. The rise of mapping knowledge domain[J]. Studies in Science of Science, 2005, 23(2): 149-154.DOI:10.16192/j.cnki.1003-2053.2005.02.002 5 王建芳, 吴清强, 张超星, 等. 基于本体的科学知识图谱分析方法研究[EB/OL].[2014-1-15]. http://ir.las.ac.cn/handle/12502/3837. WANGJ F, WUQ Q, ZHANGC X , et al. Analysis Method of Mapping Knowledge Domains based on Ontology [EB/OL].[2014-1-15]. http://ir.las.ac.cn/handle/12502/3837. 6 SINGHALA. Introducing the Knowledge Graph: Things, Not Strings[EB/OL]. [2019-1-20]. http://googleblog.blogspot.com/2012/05/ introducing-knowledge-graph-things-not.html. 7 赵军, 刘康, 何世柱, 等. 知识图谱[M]. 北京: 高等教育出版社, 2018. ZHAOJ, LIUK, HES Z, et al. Knowledge Graph[M]. Beijing: Higher Education Press, 2018. 8 秦长江, 侯汉清. 知识图谱——信息管理与知识管理的新领域[J]. 大学图书馆学报, 2009,27(1):30-37. QINC J, HOUH Q. Mapping knowledge domain-A new field of information management and knowledge management[J]. Journal of Academic Libraries, 2009, 27(1): 30-37. 9 胡泽文, 孙建军, 武夷山. 国内知识图谱应用研究综述[J]. 图书情报工作, 2013,57(3):131-137. HUZ W, SUNJ J, WUY S. Research review on application of knowledge mapping in China[J]. Library and Information Service, 2013, 57(3): 131-137. 10 刘则渊, 陈悦, 侯海燕. 科学知识图谱:方法与应用[M]. 北京: 人民出版社, 2008. LIUZ Y, CHENY, HOUH Y. Mapping Knowledge Domains Methods and Application[M]. Beijing: People’s Publishing House, 2008. 11 CHENC. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature[J]. Journal of the Association for Information Science & Technology, 2014,57(3):359-377. DOI:10.1002/asi.20317 12 CHENC, IBEKWE-SANJUANF, HOUJ. The structure and dynamics of co-citation clusters: A multiple-perspective co-citation analysis[J]. Journal of the American Society for Information Science & Technology, 2010,61(7):1386-1409. 13 汤建民, 余丰民. 国内知识图谱研究综述与评估:2004—2010年[J]. 情报资料工作, 2012(1):16-21. TANG J M, YU F M. Review and evaluation of knowledge mapping research in China: 2004 -2010[J]. Information and Documentation Services, 2012 (1): 16-21. 14 SUCHANEKF M, KASNECIG, WEIKUMG. Yago: A core of semantic knowledge[C]//International Conference on World Wide Web,WWW 2007. Banff: ACM,2007. 15 CARLSONA, BETTERIDGEJ, KISIELB, et al. Toward an architecture for never-ending language learning[C]//Twenty-Fourth Aaai Conference on Artificial Intelligence. Atlanta: AAAI Press,2010. 16 AUERS, BIZERC, KOBILAROVG, et al. DBpedia: A nucleus for a Web of open data[J]. Semantic Web, 2007,4825:11-15. DOI:10.1007/978-3-540-76298-0_52 17 BOLLACKERK D, EVANSC, PARITOSHP, et al. Freebase: A collaboratively created graph database for structuring human knowledge[C]//SIGMOD 2008. Vancouver: AMC, 2008. 18 DONGX, GABRILOVICHE, HEITZG, et al. Knowledge vault: a web-scale approach to probabilistic knowledge fusion[C]// Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. NewYork:ACM,2014. 19 XINGN, SUNX, WANGH,et al. Zhishi.me - Weaving Chinese Linking Open Data[C]//Proceedings of the 10th International Semantic Web Conference . Bonn: Springer,2011. 20 WANGZ, LIJ, WANGZ, et al. XLore: A Large-scale English-Chinese Bilingual Knowledge Graph[C]// ISWC2013. Sydney: Springer, 2013. 21 OpenKG.CN-开放的中文知识图谱[EB/OL]. [2019-3-1]. http://www.openkg.cn/. OpenKG.CN-open Chinese knowledge Graph [EB/OL]. [2019-3-1]. http://www.openkg.cn/. 22 GATTANIA, LAMBAD S, GARERAN, et al. Entity extraction, linking, classification, and tagging for social media: a wikipedia-based approach[J]. Proc VLDB Endow, 2013,6(11):1126-1137. 23 DESHPANDEO, LAMBAD S, TOURNM, et al. Building, maintaining, and using knowledge bases: A report from the trenches[C]//ACM SIGMOD International Conference on Management of Data. Newyork: ACM,2013. 24 XUM, WANGZ, BIER, et al. Discovering missing semantic relations between Entities in Wikipedia[C]//International Semantic Web Conference. Sudney:Springer,2013. DOI:10.1007/978-3-642-41335-3_42 25 WANGZ, LIJ, TANGJ. Boosting cross-lingual knowledge linking via concept annotation[C]// Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Beijing: AAAI Press, 2013. 26 LINY, LIUZ, SUNM, et al. Learning entity and relation embeddings for knowledge graph completion[C]//Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence. Austin: AAAI Press,2015. 27 XUB, XUY, LIANGJ, et al. CN-DBpedia: A Never-Ending Chinese Knowledge Extraction System[C]// International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems. Arras:Springer,2017.DOI:10.1007/978-3-319-60045-1_44 28 UniversityTsinghua,ResearchMicrosoft.Open Academic Graph[EB/OL]. [2019-3-28]. https://www.openacademic.ai/oag/. 29 JIE T. AMiner: Toward Understanding Big Scholar Data[C]// Proceedings of the Ninth ACM International Conference on Web Search and Data Mining (WSDM'16). San Francisco:ACM,2016. 30 ZENGY,WANGD S, ZHANGT L,et al.Belief Engine - Declarative[EB/OL]. [2019-3-25]. http://www.belief-engine.org/declarative/. 31 韩喆,冯岩松.北京大学中文百科知识图谱PKU-PIE 知识库[EB/OL]. [2019-3-25]. http://openkg.cn/dataset/pku-pie. HANZ,FENGY S.Peking University Chinese Encyclopedia Knowledge Graph PKU-Pie Knowledge Base [EB/OL]. [2019-3-25]. http://openkg.cn/dataset/pku-pie. 32 冯新翎, 何胜, 熊太纯, 等. “科学知识图谱”与“Google知识图谱”比较分析——基于知识管理理论视角[J]. 情报杂志, 2017,36(1):149-153. FENGX L, HES, XIONGT C, et al. Comparison and analysis of mapping knowledge domain and google knowledge graph-based on the theory of knowledge management[J]. Journal of Intelligence, 2017,36(1):149-153. 33 熊晶, 高峰, 吴琴霞. 甲骨文大规模基础数据的语义挖掘研究[J]. 现代图书情报技术, 2015,31(2):7-14. XIONGJ, GAOF, WUQ X. Research on semantic mining for large-scale oracle bone inscriptions foundation data [J]. New Technology of Library and Information Service, 2015, 31(2): 7-14. 34 HEQ. Knowledge discovery through co-word analysis[J]. Library Trends, 1999,48(1):133-159. 35 王珊, 萨师煊. 数据库系统概论[M]. 第5版.北京: 高等教育出版社, 2014. WANGS, SA S X. Introduction to Database System[M]. 5th ed. Beijing: Higher Education Press, 2014. 36 GUARINON. Formal ontology in information systems[C]//Proceedings of the first international conference (FOIS'98). Amsterdam: IOS Press, 1998. 37 ZHAOS, CHANGE. From database to semantic web ontology: An overview[J]. Lecture Notes in Computer Science, 2007,4806:1205-1214.DOI:10.1007/978-3-540-76890-6_48 38 鄂海红, 张文静, 肖思琪, 等. 深度学习实体关系抽取研究综述[J]. 软件学报, 2019,30(6):1793-1818.DOI:10.13328/j.cnki.jos.005817 E H H, ZHANGW J, XIAOS Q, et al. A survey of entity relationship extraction based on deep learning[J]. Journal of Software, 2019,30(6):1793-1818. DOI:10.13328/j.cnki.jos.005817 39 SOCHERR, HUVALB, MANNINGC D, et al. Semantic compositionality through recursive matrix-vector spaces[C]//Joint Conference on Empirical Methods in Natural Language Processing & Computational Natural Language Learning.Jeju Island: ACL, 2012. 40 SANTOSC N D, BINGX, ZHOUB. Classifying relations by ranking with convolutional neural networks[J]. Computer Science, 2015,86(86):132-137. 41 ZENGD, LIUK, LAIS, et al. Relation classification via convolutional deep neural network[C]//Proceedings of COLING 2014.Dublin:ACL, 2014. 42 ZENGD, LIUK, CHENY, et al. Distant supervision for relation extraction via piecewise convolutional neural networks[C]// EMNLP 2015,Lisbon:ACL,2015. DOI:10.18653/v1/d15-1203 43 MIWAM, BANSALM. End-to-End relation extraction using LSTMs on sequences and tree structures[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics.Berlin:ACL, 2016.DOI:10.18653/v1/p16-1105 44 ZHOUP, SHIW, TIANJ, et al. Attention-Based bidirectional long short-term memory networks for relation classification[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics. Beelin: ACL, 2016. DOI:10.18653/v1/p16-2034 45 LINY, SHENS, LIUZ, et al. Neural relation extraction with selective attention over instances[C]//ACL 2016. Berlin: Association for Computational Linguistics, 2016. DOI:10.18653/v1/p16-1200 46 HUANGY Y, WANGW Y. Deep residual learning for weakly-supervised relation extraction[C]. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing.Copenhagen: ACL, 2017. 47 CHEW, LIZ, LIUT. LTP: A Chinese language//technology platform[J]. Journal of Chinese Information Processing, 2010,2(6):13-16. 48 庄严, 李国良, 冯建华. 知识库实体对齐技术综述[J]. 计算机研究与发展, 2016,53(01):165-192. ZHUANGY, LIG L, FEN J H. A survey on entity alignment of knowledge base[J].Journal of Computer Research and Development, 2016, 53 (1) :165-192. 49 展翔. 甲骨著錄重片拾遺及指瑕[EB/OL]. [2019-3-26]. http://www.xianqin.org/blog/archives/11297.html. ZHANX. Oracle Bone Inscriptions repeated pieces collection and errors[EB/OL]. [2019-3-26]. http://www.xianqin.org/blog/archives/11297.html. 50 朱新华, 马润聪, 孙柳, 等. 基于知网与词林的词语语义相似度计算[J]. 中文信息学报, 2016,30(04):29-36. ZHUX H, MAR C, SUNL, et al. Word semantic similarity computation based on HowNet and CiLin[J]. Journal of Chinese Information Processing, 2016, 30 (4) :29-36. 51 林海伦, 王元卓, 贾岩涛, 等. 面向网络大数据的知识融合方法综述[J]. 计算机学报, 2017,40(01):1-27. LINH L, WANGY Z, JIAY T, et al. Network big data oriented knowledge fusion methods:A survey[J].Chinese Journal of Computers, 2017, 40 (1) :1-27. 52 熊晶, 王爱民, 徐建良. 基于领域本体的信息检索优化策略[J]. 计算机工程与设计, 2011,32(08):2695-2699. DOI:10.16208/j.issn1000-7024.2011.08.045 XIONGJ , WANGA M, XUJ L. Information retrieval optimization strategy based on domain ontology[J]. Computer Engineering and Design, 2011, 32(8): 2695-2699. DOI:10.16208/j.issn1000-7024.2011.08.045 |
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