DocumentCode :
3772370
Title :
Trends, Self-Similarity, and Forecasting of News Events in the Information Domain, Its Structure and Director
Author :
S.A. Lesko;D.O. Zhukov
Author_Institution :
Fed. State Budget Educ. Establ. of Higher Educ., Moscow State Univ. of Inf. Technol., Radioeng. &
fYear :
2015
Firstpage :
870
Lastpage :
873
Abstract :
To describe the structure of news information domain, we introduce the concept of a director, that is a conditional axis, the position of which is defined by averaging the directions of vectors that set the location of all news clusters centroids. To characterise the dynamics of reaching the news event, we introduce the concepts of decreasing and increasing trends of domain varying. The analysis of self-similarity in behaviour of directors and trends on the basis of the proposed model can allow detecting the periodicity of domain approaching or moving away from the point of the predicted event.
Keywords :
"Market research","Clustering algorithms","Forecasting","Predictive models","Data models","Feeds","Arrays"
Publisher :
ieee
Conference_Titel :
Smart City/SocialCom/SustainCom (SmartCity), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SmartCity.2015.178
Filename :
7463833
Link To Document :
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