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Analysis of Audience Interest and User Clustering Based on Program Tags
Fulian Yin,Xingyi Pan,Jianping Chai,Wenwen Zhang 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.11
This paper proposes an analysis method of user behavior to provide personalized program recommendation based on program tags in the field of broadcasting and television. Multidimensional Scaling Analysis is used to produce a quantitative description of viewing preferences. Hierarchical clustering is performed to determine the number of clusters, followed by K-means clustering to group the data according to audience interest in TV program tags. This divides the audience into groups with similar viewing preferences.
The Big Data Applications in Film Industry Chain
Xinran Wang,Yan Wang,Jianping Chai,Xi Feng,Ziyu Liu 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.12
Nowadays, the audiences' consumption attitudes, consumption patterns and consumer groups are all in the great changes, thus it is necessary to improve the film’s revenue by excellent script selecting, accurate market positioning, effective product marketing, and accurate forecasting of the box office. This paper introduced the application and benefit of big data in the film industry chain in terms of film making and investing, film publicity and distribution, film broadcasting and film audience, pointed out many challenges that big data encountered in China’s film industry and finally provided useful suggestions for the practitioners in the film industry of all aspects.
Combination Weighting Method Based on Maximizing Deviations and Normalized Constraint Condition
Fulian Yin,Lu Lu,Jianping Chai,Yanbing Yang 보안공학연구지원센터 2016 International Journal of Security and Its Applicat Vol.10 No.2
When the weight of each attribute is determined in the multiple attribute decision making problems, calculated by the method of subjective values or objective values solely will cause the problem that weight coefficient is not reasonable. So the paper puts forward the weightingmethod which is based on maximizing deviations and normalized constraint condition. The method integrates the subjective and objective weighting information. On the one hand, the deviation between each weight vector which is determined by the various weighting method makes the maximum of its total deviation. On the other hand, the various evaluated object integrated value makes the maximum of its total evaluated value. Thus we establish a double objective optimization model. What’s more, we deduce the weight calculation formula by solving the model. Finally we have an experimental analysis. It proves that the combination weighting methodcan reflect the relative importance of each indicators and the information that index itself contains. In other words, it can reflect the subjective and objective decisions which make the weighting results more reasonable.
A Content-Based Approach to Recommend TV Programs Enhanced with Delayering Tagging
Fulian Yin,Xingyi Pan,Huixin Liu,Jianping Chai 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.9
In response to explore how to extract the recommended items' features, a method is put forward called a Content-based TV Program Recommendation Approach Enhanced with Delayering Tagging. The Content-based approach is optimized to recommend TV programs and improved the way to extract the recommended items' features. Besides, the existing way of using supervised method to build user modeling is replaced with an unsupervised method using delayering tagging to show recommended TV program's content features and set up user preference model. After compared with Latent Factor Model and Collaborative Filtering recommendation algorithm with the same experimental data, the proposed algorithm in this paper increased the accuracy of 2.67\%, coverage rate of 3.02\% and 3.2\% of the Feature 1 value and achieved good recommendation results compared to the Latent Factor Model which revealed the best effect of recommendation.
Shu-Jun Wei,Jing Ni,Kuanyu Zheng,Zhenguo Yang,Daoyan Xie,Aisi Da,Jianping Chai,Xiujun Jiang,Shaoxiang Li 한국응용곤충학회 2018 Journal of Asia-Pacific Entomology Vol.21 No.1
The carmine spider mite, Tetranychus cinnabarinus (Boisduval), is a serious phytophagous mite damaging importantcrops and can rapidly develop resistance to acaricides. Mitochondrial ATP synthase (F1F0 ATP synthase)is an important target site of acaricides. The role of ATP synthase in acaricide resistance remains unclear at themolecular level. In this study, twelve full-length cDNAs of ATP synthase genes were cloned and characterizedfrom T. cinnabarinus and their expression levels were determined for both progargite-resistant and susceptiblestrains. The effect of propargite exposure on gene expression was also evaluated. Analyses of gene expressionrevealed that TcATPsynU-2, TcATPsynF0-2 and TcATPsynF0-4 were significantly down-regulated in the progargite-resistant strain. TcATPsynF0-2 and TcATPsynF0-4 had a strong response to progargite exposure. Theresults suggest that lower levels of TcATPsynU-2, TcATPsynF0-2 and TcATPsynF0-4 expression might be related topropargite-resistance observed in the resistant T. cinnabarinus. This is the first attempt to identify specific ATPasegenes involved in propargite resistance in T. cinnabarinus.