Uncertainty Analysis for the Keyword System of Web Events

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. Appare...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2016-06, Vol.46 (6), p.829-842
Main Authors: Xuan, Junyu, Luo, Xiangfeng, Zhang, Guangquan, Lu, Jie, Xu, Zheng
Format: Article
Language:English
Subjects:
Algorithm design and analysis
Association rules
Cybernetics
Earthquakes
Entropy
Evolution
Hierarchies
Measurement uncertainty
Recommendations
Recommender systems
Representations
Sales management
Sales prospecting
Semantics
Social event
Teleconferencing
Uncertainty
uncertainty analysis
Web event
Web mining
Webpage recommendation
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Summary: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 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 Web event representation and Shannon entropy, we identify the different levels of semantic uncertainty, and construct a semantic pyramid (SP) to express the uncertainty hierarchy of a Web event. Finally, an SP-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 applied to Webpage recommendations.
ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2015.2470645