Jianping Chai

Impact analysis on three-dimensional indoor location technology

This paper proposed an impact analysis framework of three-dimensional indoor location technology based on RSSI. The impact analysis model is set to compare the location precision under different types of noise. The result illustrate that the designed impact analysis tool achieves the perfect three-dimensional indoor location results combined cost, location accuracy with filter. To reduce the impact of the noise, the secondary location which built various propagation models for different types of environments has been used. And the location accuracy is greatly improved.

A Framework Analysis of Measuring the Index Node Considering Local and Global Networks

This paper proposes a solution using multi-index method to evaluate node importance locally and globally with adjusted parameters in the network by considering several evaluation indexes. Especially, it adheres to the principles that the node importance of the network is relevant to the value of the node itself together with the centrality of neighbor nodes from a local point of view. Moreover, this paper considers both spreading information and speed of node in dynamic network. The chief influence on adjusted parameters in different network has been estimated. We can rank the influence of users and analyze their tags of interest from the result. In addition, we can make valuable classification of users and improve the service for more personalized services, which is very important for data mining.

Research of users' viewing habits based on clustering method

With the development of value-added services in cable digital TV, user behavior analysis has important practical significance in improving stickiness and implementation of personalized marketing. Based on real viewing data collected by software in set-top box, this paper adopts clustering method to analyze viewing habit in a particular region of Shanxi Province. The results show that the prime time in this region is from 7PM to 11PM, and the difference between overall user viewing on workday and weekend is not significant. Users favorite viewing hour is from 9PM to 10PM and users who watch TV longer and more frequently are more accustomed to watching TV in prime time.

Research on visualization of communication network in social topic

Visualization technology helps people find much information which is difficult to dig up with the conventional statistical methods, understand the dynamic variation law, so as to predict the development and the results of network better. In this paper, based on the relevant knowledge of complex network theory and communication, we use the huge amounts of data in the social network to set up communication network model in social topic, and improve the mechanical model of classical algorithm to realize the dynamic real-time visualization in the process of topic communication. The dynamic visualization of single and multiple topics explain the process and mechanism of information transmission intuitively.