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Publications (13)
Currently, many intelligence systems contain the texts from multi-sources, e.g., bulletin board system posts, tweets and news. These texts can be “comparative” since they may be semantically correlated and thus provide us with different perspectives toward the same topics or events. To better organize the multi-sourced texts and obtain more compreh...
Currently, many intelligence systems contain the texts from multi-sources, e.g., bulletin board system (BBS) posts, tweets and news. These texts can be ``comparative'' since they may be semantically correlated and thus provide us with different perspectives toward the same topics or events. To better organize the multi-sourced texts and obtain more...
This paper makes the first step towards mining citywide traffic congestion correlation by utilizing traffic related information from social media. Traffic congestion correlation mining, namely studying which road segments close to each other are highly likely to occur congestion simultaneously, is especially important to help many real applications...
Online business intelligence systems often collect the texts from different sources, such as social media and news websites that can be heterogeneous in practice. These collections bring the difficulties of managing and organizing the comprehensive information hidden in different texts of the system. To more effectively organize the multisourced te...
Estimating urban traffic conditions of an arterial network with GPS probe data is a practically important while substantially challenging problem, and has attracted increasing research interests recently. Although GPS probe data is becoming a ubiquitous data source for various traffic related applications currently, they are usually insufficient fo...
Social networks contain a large amount of information on transportation, e.g., traffic accidents, congestions, and vehicles. Such information is the original ideas of people with respect to real-world transportation issues, and detecting communities on the topic of transportation from the information will benefit many ITS applications. However, rea...
One of the key challenges in large attributed graph clustering is how to select representative attributes. Previous studies introduce user-guided clustering methods by letting a user select samples based on his/her knowledge. However, due to knowledge limitation, a single user may only pick out the samples that s/he is familiar with while ignore th...
Utilising both key mathematical tools and state-of-the-art research results, this text explores the principles underpinning large-scale information processing over networks and examines the crucial interaction between big data and its associated communication, social and biological networks. Written by experts in the diverse fields of machine learn...
One of the key challenges in large attributed graph clustering is how to select representative attributes. Previous studies introduce user-guided clustering methods by letting a user select samples based on his/her knowledge. However, due to knowledge limitation, a single user may only pick out the samples that s/he is familiar with while ignore th...
On Twitter, People do not only find new friends by following others, but also propagation the information by retweeting. So, we can not measure the users’ influence only by following relationships easily, also, it is not reasonable to measure tweets’ popularity by the number of retweets. In this paper, a novel random walk model was proposed to meas...
An emerging hyper-world encompasses all human activities in a social-cyber-physical space. Its power derives from the Wisdom Web of Things (W2T) cycle, namely, "from things to data, information, knowledge, wisdom, services, humans, and then back to things."' The W2T cycle leads to a harmonious symbiosis among humans, computers, and things, which ca...
With the booming of social media, sentiment analysis has developed rapidly in recent years. However, only a few studies focused on the field of transportation, which failed to meet the stringent requirements of safety, efficiency, and information exchange of intelligent transportation systems (ITSs). We propose the traffic sentiment analysis (TSA)...