Uncertainty Analysis for the Keyword System of Web Events

Junyu Xuan, Xiangfeng Luo, Guangquan Zhang, Jie Lu, Zheng Xu
2016 IEEE Transactions on Systems, Man & Cybernetics. Systems  
Webpage recommendations for hot web events can assist people to easily follow the evolution of these web events. At the same time, there are different levels of semantic uncertainty underlying the amount of webpages for a web event, such as recapitulative information and detailed information. Apparently, the grasp of the semantic uncertainty of web events could improve the satisfactoriness of webpage recommendations. However, traditional hit-rate-based or clustering-based webpage recommendation
more » ... methods have overlooked these different levels of semantic uncertainty. In this paper, we propose a framework to identify the different underlying levels of semantic uncertainty in terms of web events, and then utilize these for webpage recommendations. Our idea is to consider a web event as a 'system' composed of different keywords, and the uncertainty of this keyword system is related to the uncertainty of the particular web event. Based on Keyword Association Linked Network (KALN) web event representation and Shannon Entropy, we identify the different levels of semantic uncertainty, and construct a semantic pyramid to express the uncertainty hierarchy of a web event. Finally, a semantic pyramid-based webpage recommendation system is developed. Experiments show that the proposed algorithm can significantly capture the different levels of the semantic uncertainties of web events and it can be used for webpage recommendations.
doi:10.1109/tsmc.2015.2470645 fatcat:aagjyntyjrb4tdbzdia5c2obnu