一种情感极性感知的信任模型

doi:10.3969/j.issn.1001-2400.2015.02.032

Abstract

Abstract: Focusing on the discordance between text comments and ratings, a synthetical evaluation generating algorithm is proposed by using sentiment polarity analysis, and a trust computation model is constructed based on the HMM. The optimal hidden trust state sequence is found according to the observation sequence which is a synthetical evaluation sequence. The probability of an entity in the most credible state is the trust value. In this model, the precision of trust computation is improved, and trust dynamics is reflected. Finally, satisfactory results are obtained with simulated experiments.

Key words: hidden Markov model, sentiment polarity, comments, trust

CLC Number:

TP393.2

LI Hui;MA Jianfeng. Sentiment polarity-awareness trust model [J].J4, 2015, 42(2): 193-198.

References

［1］ Jsang A, Ismail R, Boyd C. A Survey of Trust and Reputation Systems for Online Service Provision［J］. Decision Support Systems, 2007, 43(2): 618-644. ［2］ Thirunarayan K, Anantharam P, Henson C, et al. Comparative Trust Management with Applications: Bayesian Approaches Emphasis［J］. Future Generation Computer Systems, 2014, 31(2): 182-199. ［3］ Xia Hui, Jia Zhiping, Sha E H. Research of Trust Model based on Fuzzy Theory in Mobile ad hoc Networks［J］. IET Information Security, 2014, 8(2): 88-103. ［4］ Bonatti P A, Oliveira E, Sabater-Mir J, et al. On the Integration of Trust with Negotiation, Argumentation and Semantics［J］. Knowledge Engineering Review, 2014, 29(1): 31-50. ［5］ Haydar C, Roussanaly A, Boyer A. Local Trust Versus Global Trust Networks in Subjective Logic［C］//Proceedings of the IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology. Atlanta: IEEE Communications Society, 2013: 29-36. ［6］ Mui L. Computational Models of Trust and Reputation: Agents, Evolutionary Games, and Social Networks［D］. Boston: Massachusetts Institute of Technology, 2003. ［7］ Xu T, Peng Q, Cheng Yin. Identifying the Semantic Orientation of Terms Using S-HAL for Sentiment Analysis［J］. Knowledge Based on Systems, 2012, 35: 279-289. ［8］ Rabiner L. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition［J］. Proceedings of the IEEE, 1989, 77(2): 257-286. ［9］ Baum L E, Petrie T. Statistical Inference for Probabilistic Functions of Finite Markov Chains［J］. The Annals of Mathematical Statistics, 1966, 37(6): 1554-1563. ［10］ Manning C D, Surdeanu M, Bauer J, et al. The Stanford CoreNLP Natural Language Processing Toolkit［C］//Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. Baltimore: System Demonstrations, 2014: 55-60. ［11］ Baccianella S, Esuli A, Sebastiani F. SentiWordNet 3.0: an Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining［C］//Proceedings of the International Conference on Language Resources and Evaluation. Valletta: European Language Resources Association, 2010: 2200-2204. ［12］ Moe M E G, Helvik B E, Knapskog S. J. Comparison of the Beta and the Hidden Markov Models of Trust in Dynamic Environments［C］//Proceedings of the Third IFIP WG 11.11 International Conference. Heidelberg: Springer, 2009: 283-297. ［13］ Ismail R, Jsang A. The Beta Reputation System［C］//Proceedings of the 15th Bled Conference on Electronic Commerce. Hudson: AIS, 2002: 891-900.

[1]	WAN Pengwu,YAO Yuanyuan,YAN Qianli,CHEN Yufei. Passive localization based on energy-time-frequency information fusion [J]. Journal of Xidian University, 2021, 48(6): 105-114.
[2]	SUN Qian,ZHANG Jiarui,GAO Ling,WANG Yuxiang,YANG Jianfeng. Health prediction algorithm for edge layer nodes [J]. Journal of Xidian University, 2020, 47(3): 32-39.
[3]	XIE Lixia,WEI Ruixin. IoT Node trust comprehensive evaluation model [J]. Journal of Xidian University, 2019, 46(4): 58-65.
[4]	CHEN Chu. RFCcertDT: a testing tool for certificate validation in SSL/TLS [J]. Journal of Xidian University, 2019, 46(3): 20-25.
[5]	YAN Qianli,WAN Pengwu,LU Guangyue,HUANG Qiongdan,WANG Jin,LI Yixiao. Passive localization of the signal source based on RSS and TDOA combination in the non-line-of-sight environment [J]. Journal of Xidian University, 2019, 46(3): 180-188.
[6]	LIU Jiao;SUN Cong;MA Jianfeng;JIAO Zhengda. Remote authorization protocol for vehicle diagnosis using trusted platform measurements [J]. Journal of Xidian University, 2017, 44(3): 49-54+119.
[7]	LIANG Hongquan;WU Wei. Secure link status routing protocol based on node trustworthiness [J]. Journal of Xidian University, 2016, 43(5): 121-127.
[8]	GUO Jingjing;MA Jianfeng. Trust recommendation algorithm for the virtual community based Internet of Things(IoT) [J]. J4, 2015, 42(2): 52-57+179.
[9]	ZHANG Guanghua;ZHANG Yuqing;LIU Xuefeng;YAN Jingbo. Behavior trust fuzzy evaluation model [J]. J4, 2015, 42(1): 29-34.
[10]	MENG Xianjia;MA Jianfeng;LU Di;WANG Yichuan. Trust and behavioral modeling based two layer service selection [J]. J4, 2014, 41(4): 198-204.
[11]	LI Qing;DONG Qingkuan;ZHAO Lei. Modified forward cloud generator in the cloud model [J]. J4, 2013, 40(5): 169-174+180.
[12]	LIU Yuling;DU Ruizhong;FENG Jianlei;TIAN Junfeng. Trust model of software behaviors based on check point risk assessment [J]. J4, 2012, 39(1): 179-184+190.
[13]	SUO Yan;XU Xiaoyan;ZHANG Yusen;ZHANG Tao;GUI Jingjing;YANG Li;YUE Kang. Key-insulated component property-based attestation [J]. J4, 2011, 38(4): 11-19.
[14]	CHEN Chang-hong;ZHAO Heng;LIANG Ji-min;JIAO Li-cheng. Influence of feature selection on FHMM [J]. J4, 2010, 37(5): 934-940.
[15]	ZHANG Zhi-yong1;2;PEI Qing-qi1;YANG Lin3;MA Jian-feng1. Attestation proxy party-supported remote attestation model and its secure protocol [J]. J4, 2009, 36(1): 58-63.

Sentiment polarity-awareness trust model

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Metrics

Comments

Recommended 0