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Social and Behavioral Sciences Commons

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Physical Sciences and Mathematics

Singapore Management University

Anomaly detection

Articles 1 - 5 of 5

Full-Text Articles in Social and Behavioral Sciences

Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim Oct 2018

Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

As road transportation supports both economic and social activities in developed cities, it is important to maintain smooth traffic on all highways and local roads. Whenever possible, traffic congestions should be detected early and resolved quickly. While existing traffic monitoring dashboard systems have been put in place in many cities, these systems require high-cost vehicle speed monitoring instruments and detect traffic congestion as independent events. There is a lack of low-cost dashboards to inspect and analyze the lifecycle of traffic congestion which is critical in assessing the overall impact of congestion, determining the possible the source(s) of congestion and its …


Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin Dec 2014

Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …


Challenges And Opportunities In Taxi Fleet Anomaly Detection, Rijurekha Sen, Rajesh Krishna Balan Nov 2013

Challenges And Opportunities In Taxi Fleet Anomaly Detection, Rijurekha Sen, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

To enhance fleet operation and management, logistics companies instrument their vehicles with GPS receivers and network connectivity to servers. Mobility traces from such large fleets provide significant information on commuter travel patterns, traffic congestion and road anomalies, and hence several researchers have mined such datasets to gain useful urban insights. These logistics companies, however, incur significant cost in deploying and maintaining their vast network of instrumented vehicles. Thus research problems, that are not only of interest to urban planners, but to the logistics companies themselves are important to attract and engage these companies for collaborative data analysis. In this paper, …


Anomaly Detection On Social Data, Hanbo Dai Jun 2013

Anomaly Detection On Social Data, Hanbo Dai

Dissertations and Theses Collection (Open Access)

The advent of online social media including Facebook, Twitter, Flickr and Youtube has drawn massive attention in recent years. These online platforms generate massive data capturing the behavior of multiple types of human actors as they interact with one another and with resources such as pictures, books and videos. Unfortunately, the openness of these platforms often leaves them highly susceptible to abuse by suspicious entities such as spammers. It therefore becomes increasingly important to automatically identify these suspicious entities and eliminate their threats. We call these suspicious entities anomalies in social data, as they often hold different agenda comparing to …


Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin Dec 2012

Visualization For Anomaly Detection And Data Management By Leveraging Network, Sensor And Gis Techniques, Zhaoxia Wang, Chee Seng Chong, Rick S. M. Goh, Wanqing Zhou, Dan Peng, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

This paper studies the importance of visualization for discerning and interpreting patterns of data and its application for solving real problems, such as anomaly detection and data management. There are various ways to realize visualization to cater to the needs of numerous real life applications. Depending on needs, a combination of some of these ways may be required for presenting an effective visualization. The authors present visualization schemes for anomaly detection/condition monitoring and data management by leveraging network techniques and combining them with modern techniques such as sensor, database, mobile communication, GPS and GIS techniques. Two case studies are presented …