User and Entity Behavior Analysis under Urban Big Data

User-Generated Big Data and Urban Morphology

Research and Application of Network User Behavior Data Mining under the Background of Big Data

In this paper, the author studies the application of network user behavior data mining under the background of big data. In this research work we focused mainly on the precise mobility profile building thorough trajectory and behavioral pattern mining using the GSM CGI Cell-ID, where all the concerned issues like precise spatial extraction, stay points detection and mobility profiling are addre...

Analysis of User Behavior under E Dialogs

We focus on developing an account of user behavior under error conditions, working with annotated data from real human-machine mixed initiative dialogs. In particular, we examine categories of error perception, user behavior under error, effect of user strategies on error recovery, and the role of user initiative in error situations. A conditional probability model smoothed by weighted ASR erro...

Analysis of big data set of urban traffic data

Modern vehicles are increasingly capable of reporting location and status information in real time using GPSenabled on-board telemetry boxes which connect directly into a vehicle’s control and diagnostic systems. We perform an exploratory analysis of such data obtained from a vehicle operating in a large UK urban area. The primary objective is to devise informative summary statistics that allow...

Entity Resolution in a Big Data Framework

Resource Description Framework (RDF)1 is a data model that can be used to publish semistructured data visualized as directed graphs. An example is Dataset 1 in Fig. 1. Nodes in the graph represent entities and edges represent properties connecting these entities. Two nodes may refer to the same logical entity, despite being syntactically disparate. For example, the entity Mickey Beats in Datase...