A Novel Ontology Construction and Reasoning Approach Based on the Case Investigation
International Journal of Data Science and Analysis
Volume 5, Issue 6, December 2019, Pages: 148-158
Received: Nov. 8, 2019;
Accepted: Dec. 11, 2019;
Published: Dec. 31, 2019
Views 716 Downloads 160
Han Zhong, College of Information Technology and Network Security, People’s Public Security University of China, Beijing, China
Hongzhou Zhang, College of Information Technology and Network Security, People’s Public Security University of China, Beijing, China
Jianqian Zhang, College of Information Technology and Network Security, People’s Public Security University of China, Beijing, China
Ziyang Yuan, College of Information Technology and Network Security, People’s Public Security University of China, Beijing, China
The big data has become a key component for intelligent systems and it is very important about data mining and cognitive reasoning in the field of criminal data analysis. Modeling of investigation knowledge is very important to realize the semantic retrieval, knowledge discovery, information push and classification for case data. Ontology modeling combined with the characteristics of the case in the investigation process, a method of ontology construction based on investigation knowledge is proposed in this paper. It builds an organization system of the investigation process at the first, which is described in stages by collecting terminology. Then the ontology of investigation knowledge is constructed. In addition, an instance is added for verification to describe the investigation process in detail. The method has a good advantage of describing the detection process quickly and integrate knowledge according to different investigation stages, formulating a standardized organization mode and providing standardized knowledge assistance in the investigation process.
A Novel Ontology Construction and Reasoning Approach Based on the Case Investigation, International Journal of Data Science and Analysis.
Vol. 5, No. 6,
2019, pp. 148-158.
Xianjiao Zeng, Guangquan Xu, Xi Zheng, Yang Xiang, and Wanlei Zhou, E-AUA: An Efficient Anonymous User Authentication Protocol for Mobile IoT, IEEE Internet of Things Journal 6 (2): 1506-1519, April 2019. DOI: 10.1109/JIOT.2018.2847447.
Guangquan Xu, Yao Zhang, Arun K Sangaiah, Xiaohong Li, Aniello Castiglione, Xi Zheng, CSP-E^2: An abuse-free Contract Signing Protocol with low-storage TTP for energy-efficient electronic transactions ecosystems, Information Sciences 476 (2019) 505-515, DOI: 10.1016/j.ins.2018.05.022.
Guangquan Xu, Jia Liu, Yanrong Lu, Xianjiao Zeng, Yao Zhang, Xiaoming Li, A novel efficient MAKA protocol with desynchronization for anonymous roaming service in Global Mobility Networks, Journal of Network & Computer Applications 107 (2018) 83-92.
Zhenhu Ning, Guangquan Xu, Naixue Xiong, Yongli Yang, Changxiang Shen, Emmanouil Panaousis, Hao Wang, Kaitai Liang. TAW: Cost-Effective Threshold Authentication with weights for Internet of Things. IEEE Access 7: 30112-30125 (2019).
Abdulaziz Alzubaidi, Swarup Roy, Jugal Kalita. A data reduction scheme for active authentication of legitimate smartphone owner using informative apps ranking, Digital Communications and Networks, 9 (2018) 1-9.
Latif Ullah Khan. Visible light communication: Applications, architecture, standardization and research challenges, Digital Communications and Networks, 3 (2017) 78-88.
Matthew L. Hale, Kerolos Lotfy, Rose F. Gamble, Charles Walter, Jessica Lin. Developing a platform to evaluate and assess the security of wearable devices, Digital Communications and Networks, 10 (2018) 1-13.
Zhang Pengli, Chen Shiqu. Criminal investigation [M]. Beijing: Mass Press, 2010.5.
Hao Hongkui. Discipline Status of Investigative Subject [J]. Public Security Education, 2002, (4).
Bai L, Lao S Y, Smeaton A F. Video Semantic Content Analysis Based on Ontology [C] International Machine Vision and Image Processing Conference, Maynooth, Ireland, September 5-7, 2007.
LI Zhi-yi, LI De-hui, ZHAO Peng-wu. Research on Automatic Extraction of Dontology Concept and Its Relation in E-commerce [J]. information science, 2018, 36 (7): 85-90.
WEN Liang，LI Juan，LIU Zhiying，JIN Yaohong. A Method of Knowledge Representation and Ontology Modeling Based on Hierarchical Network of Concepts [J]. Journal of Chinese Information Processing, 2018, 32 (4): 66-73.
WANG Mengxiang, RAO Qi, GU Cheng, WANG Houfeng. Metaphorical Knowledge Expression and Acquisition for Chinese Nouns [J]. Journal of Chinese Information Processing, 2017, 31 (6): 01-09.
Yang Xiaohui, Wan Rui, Zhang Haibin, Zeng Yifu, Liu Qiao. Semantical Symbol Mapping Embedding Learning Algorithm for Knowledge Graph [J]. Journal of Computer Research and Development, 2018, 55 (8): 1773-1784.
JIANG Tianwen, QIN Bing, LIU Ting. Open Domain Knowledge Reasoning for Chinese Based on Representation Learning [J]. Journal of Chinese Information Processing, 2018, 32 (3): 34-41.
GUAN Sai-Ping, JIN Xiao-Long, JIA Yan-Tao, WANG Yuan-Zhuo, CHENG Xue-Qi. Knowledge Graph Oriented Knowledge Inference Methods: A Survey [J]. Journal of Software, 2018, 29 (10): 01-29.
Kaneiwa, K. and Mizoguchi, R., Distributed reasoning with ontologies and rules in order-sorted logic programming, Journal of Web Semantics 7 (3), pp. 252–270, 2009.
XU Wei, LI Kai, WANG Yanlong. Ship cabin layout design ontology model oriented to semantic reasoning application [J]. Journal of Dalian University of Technology. 2018, 58 (5): 479-486.
Ma L., Yu H., Chen G., Cao L., Zhao Y., Research on Construction and SWRL Reasoning of Ontology of Maize Diseases. In: Li D., Chen Y. (eds) Computer and Computing Technologies in Agriculture VI. CCTA 2012. IFIP Advances in Information and Communication Technology, vol 393. Springer, Berlin, Heidelberg, 2013.
Singh S., Kaur R., Analyzing and displaying of crime hotspots using fuzzy mapping method. International Journal of Computer Applications, 103 (1): 25-28, 2014.
WANG Jiahai, CHEN Yu. Data-driven Job Shop production scheduling knowledge mining and optimization [J]. Computer Engineering and Applications, 2018, 54 (1): 264-270.
Anna L Buczak and Christopher M Gifford. 2010. Fuzzy association rule mining for community crime pattern discovery. In ACM SIGKDD Workshop on Intelligence and Security Informatics. ACM, 2.
Lau, R. Y., Y. Xia, and Y. Ye (2014). A probabilistic generative model for mining cybercriminal networks from online social media. IEEE computational intelligence magazine 9 (1), 31–43.
CHEN Zhigang, LIU Zhikun, YANG Lujing. Modeling of a PO for Tactical Intention Recognition Based on PR-OWL [J]. Ship Electronic Engineering, 2015 (2): 86-89.
Mittal, S., P. K. Das, V. Mulwad, A. Joshi, and T. Finin (2016). Cybertwitter: Using twitter to generate alerts for cybersecurity threats and vulnerabilities. In Advances in Social Networks Analysis and Mining (ASONAM), 2016 IEEE/ACM International Conference on, pp. 860–867. IEEE.
TANG Zai-jiang, XUE Xiang-zhong, XUE Qing, HUO Biao. Operational Action Ontology Modeling and Semantic Reasoning Based on Ontology [J]. Computer Simulation, 2018, 35 (6): 1-6.
BAI Liang, LAO Song-yang, LIU Hai-tao, BU Jiang, CHEN Jian-yun. Video Semantic Content Analysis Using Extensions to OWL [J]. JOURNAL OF NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY, 2010, 32 (2): 79-84.
Jie Ma; Jing Zhang; Hong Lu; XiangyangXue; "Semantic Information Extraction of Video Based on Ontology and Inference," Semantic Computing, 2007. ICSC 2007. International Conference on, vol., no., pp. 721-726, 17-19 Sept. 2007.
Heum Park, SunHo Cho, and Hyuk-Chul Kwon. Cyber Forensics Ontology for Cyber Criminal Investigation. LNICST 8, 160-165, 2009.
Raj Kumar Vishwakarma, Ravi Shankar. Modeling Brain and Behavior of a Terrorist through Fuzzy logic and Ontology. Proceedings of the 2013 IEEE IEEM, 2-7, 2013.
Banczyk, K.; Krawczyk, H.; "Ontology Oriented Threat Detection System (OOTDS)," Dependability of Computer Systems, 2009. DepCos-RELCOMEX '09. Fourth International Conference on, vol., no., pp. 144-151, June 30 2009-July 2 2009.
Mirna El Ghosh, Hala Naja, Habib Abdulrab, Mohamad Khalil. Towards a Legal Rule-Based System Grounded on the Integration of Criminal Domain Ontology and Rules. 21th International Conference on Knowledge Based and Intelligent Information and Engineering Systems, 632-642, 2013.
Horrocks, I., Kutz, O., Sattler, U., The even more irresistible SROIQ, In Proc. of the 10th Int. Conf. On Principles of Knowledge Representation and Reasoning, 2006, pp. 57-67, AAAI Press.
Xu Z M, Cao X, Dong Y S, Su W P. Formal approach and automated tool for translating ER schemata into OWL ontologies. Proceedings of the 8th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2004), Sydney, Australia, 2004. Springer, 464-476, 2004.
Brank J, Grobelnik M., Mladenic D. A survey of ontology evaluation techniques. Proceedings of the 4th Conference on Data Mining and Data Warehouses (SiKDD 2005), Ljubljana, Slovenia, 2005: 166-169.