A Latent-Dirichlet-Allocation Based Extension for Domain Ontology of Enterprise’s Technological Innovation


  • Qianqian Zhang Beijing Jiaotong University
  • Shifeng Liu Beijing Jiaotong University
  • Daqing Gong Beijing Jiaotong University
  • Qun Tu Beijing Jiaotong University


Latent Dirichlet Allocation (LDA), ontology extension, enterprise’s technological innovation, semantic web, text mining


This paper proposed a method for building enterprise's technological innovation domain ontology automatically from plain text corpus based on Latent Dirichlet Allocation (LDA). The proposed method consisted of four modules: 1) introducing the seed ontology for domain of enterprise's technological innovation, 2) using Natural Language Processing (NLP) technique to preprocess the collected textual data, 3) mining domain specific terms from document collections based on LDA, 4) obtaining the relationship between the terms through the defined relevant rules. The experiments have been carried out to demonstrate the effectiveness of this method and the results indicated that many terms in domain of enterprise's technological innovation and the semantic relations between terms are discovered. The proposed method is a process of continuously cycles and iterations, that is the obtained objective ontology can be re-iterated as initial seed ontology. The constant knowledge acquisition in the domain of enterprise's technological innovation to update and perfect the initial seed ontology.


Bisson, G.; Nédellec, C. Canamero, D.(2000); Designing Clustering Methods for Ontology Building-The Mo'K Workbench, ECAI workshop on ontology learning, 31, 2000.

Blei, D.M.; Ng, A.Y.; Jordan, M.I. (2003); Latent dirichlet allocation, Journal of machine Learning research, 3(Jan), 993-1022, 2003.

Bradford, R.B. (2006); Relationship discovery in large text collections using latent semantic indexing, Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, 2006.

Bradford, R.B. (2005); Efficient discovery of new information in large text databases, International Conference on Intelligence and Security Informatics, 374-380, 2005. https://doi.org/10.1007/11427995_31

Burgelman, R.A.; Maidique, M.A.; Wheelwright, S.C. (1996); Strategic Management of Technology and Innovation, Chicago,IL:lrwin, 1996.

Cimiano, P.; and Völker, J. (2005); text2onto, International conference on application of natural language to information systems, 227-238, 2005.

Colace, F.; De Santo, M.; Greco, L.; Amato, F.; Moscato, V.; Picariello, A. (2014); Terminological ontology learning and population using latent dirichlet allocation, Journal of Visual Languages & Computing, 25(6), 818-826, 2014. https://doi.org/10.1016/j.jvlc.2014.11.001

Dai, Y.; Wu, W.; Zhou, H.B.; Zhang, J.; Ma, F.Y. (2018); Numerical simulation and optimization of oil jet lubrication for rotorcraft meshing gears, International Journal of Simulation Modelling, 17(2), 318-326, 2018. https://doi.org/10.2507/IJSIMM17(2)CO6

Dai, Y.; Zhu, X.; Zhou, H.; Mao, Z.; Wu, W.(2018); Trajectory tracking control for seafloor tracked vehicle by adaptive neural-fuzzy inference system algorithm, International Journal of Computers, Communications & Control 13(4), 465-476, 2018. https://doi.org/10.15837/ijccc.2018.4.3267

De Knijff, J.; Frasincar, F.;Hogenboom, F. (2013); Domain taxonomy learning from text: The subsumption method versus hierarchical clustering Data & Knowledge Engineering, 83, 54-69, 2013. https://doi.org/10.1016/j.datak.2012.10.002

Dellschaft, K; Staab, S. (2008); Strategies for the evaluation of ontology learning, Ontology Learning and Population, 167, 253-272, 2008.

Deng, L; Wang, X; Lin, Y; He, F.Z. (2005); Model of Multiple Fuzzy Synthetical Evaluation for Enterprise Technology Innovation, Journal of Chongqing University (Natural Science Edition), 7, 004, 2005.

Guan, J.C.; Yam, R.C.; Mok, C.K.; Ma, N. (2006); A study of the relationship between competitiveness and technological innovation capability based on DEA models, European Journal of Operational Research, 170(3), 971-986, 2006. https://doi.org/10.1016/j.ejor.2004.07.054

Guarino, N.; Poli, R. (1993); Toward principles for the design of ontologies used for knowledge sharing, In Formal Ontology in Conceptual Analysis and Knowledge Representation, Kluwer Academic Publishers, in press. Substantial revision of paper presented at the International Workshop on Formal Ontology, 1993.

Hennig, L. (2009); Topic-based multi-document summarization with probabilistic latent semantic analysis, Proceedings of the International Conference RANLP-2009, 144-149, 2009.

Hofmann, T. (2001); Unsupervised learning by probabilistic latent semantic analysis, Machine learning, 42(1-2), 177-196, 2001. https://doi.org/10.1023/A:1007617005950

Khan, L.; Luo, F. (2002); Ontology construction for information selection, Proceeding of Tools with Artificial Intelligence, 122-127, 2002.

Lee, C.S.; Kao, Y.F.; Kuo, Y.H.; Wang, M. H. (2007); Automated ontology construction for unstructured text documents, Data & Knowledge Engineering, 60(3), 547-566, 2007. https://doi.org/10.1016/j.datak.2006.04.001

Liu, Q.; Zhang, H.; Yu, H.; Cheng, X. (2004); Chinese lexical analysis using cascaded hidden markov model, Journal of Computer Research and Development, 41(8), 1421-1429, 2004.

Ni, N.; Liu, K.; Li, Y. (2011); An automatic multi-domain thesauri construction method based on lda, 2011 10th International Conference on Machine Learning and Applications Workshops, 235-240, 2011.

Raghuveer, K. (2012); Legal documents clustering using latent dirichlet allocation, International Journal of Applied Information Systems, 2(1), 34-37, 2012.

Saunila, M.; Ukko, J. (2012); A conceptual for the measurement of innovation capability and its effects, Baltic Journal of Management, 7(4), 355-375, 2012. https://doi.org/10.1108/17465261211272139

Tho, Q.T.; Hui, S.C.; Fong, A.C.M.; Cao, T.H. (2006); Automatic fuzzy ontology generation for semantic web, IEEE transactions on knowledge and data engineering, 18(6), 842-856, 2006. https://doi.org/10.1109/TKDE.2006.87

Tsai, M.T; Chuang, S.S; Hsieh W.P. (2008); Using Analytic Hierarchy Process to Evaluate Organizational Innovativeness in High-Tech Industry, Decision Sciences Institute 2008 Annual Meeting (DSI), 1231-1236, 2008.

Wang, T. J; Chang, L. (2011); The development of the enterprise innovation value diagnosis system with the use of systems engineering, System Science and Engineering (ICSSE), 2011 International Conference on IEEE, 373-378, 2011.

Wang, C; Lu, I; Chen, C. (2008); Evaluating firm technological innovation capability under uncertainty, Technovation, 28(6), 349-363, 2008. https://doi.org/10.1016/j.technovation.2007.10.007

Wei, W.; Guo, C.; Chen, J.; Tang, L.; Sun, L. (2017); CCODM: conditional co-occurrence degree matrix document representation method, Soft Computing, 1-17, 2017.

Wei, W.; Guo, C.; Chen, J.;Zhang, Z. (2017); Textual topic evolution analysis based on term co-occurrence: A case study on the government work report of the State Council (1954-2017), Intelligent Systems and Knowledge Engineering, 1-6, 2017.

Yeh, J.H.; Yang, N. (2008); Ontology construction based on latent topic extraction in a digital library, International Conference on Asian Digital Libraries, 93-103, 2008. https://doi.org/10.1007/978-3-540-89533-6_10

Yliherva, J. (2004); Management model of an organization's innovation capabilities; development of innovation capabilities as part of the management system, dissertation, Department of Industrial Engineering and Management, University of Oulu.

Zhang, W.; Zhang, Z.; Chao, H.C.; Tseng, F.H. (2018); Kernel mixture model for probability density estimation in Bayesian classifiers. Data Mining and Knowledge Discovery, Data Mining and Knowledge Discovery, 32(3), 675-707, 2018. https://doi.org/10.1007/s10618-018-0550-5

Zhang, W.; Zhang, Z.; Qi, D.; Liu, Y. (2014); Automatic crack detection and classification method for subway tunnel safety monitoring, Sensors, 14(10), 19307-19328, 2014. https://doi.org/10.3390/s141019307

Zhao, W.; Zeng, Y. (2011); Construction and design of evaluation index system of innovative enterprises on innovative capacities, Science and Technology Management Research, 1, 005, 2011.

Zavitsanos, E.; Paliouras, G.; Vouros, G.A.; Petridis, S. (2010); Learning subsumption hierarchies of ontology concepts from texts, Web Intelligence and Agent Systems: An International Journal, 8(1), 37-51, 2010.

Zavitsanos, E.; Paliouras, G.; Vouros, G.A.; Petridis, S. (2010); Discovering subsumption hierarchies of ontology concepts from text corpora, Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence, 402-408, 2007.



Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.