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In large-scale online service systems, numerous Key Performance Indicators (KPIs), such as service response time and error rate, are gathered in a time-series format. KPI Anomaly Detection (KAD) is a critical data mining problem due to its widespread ...

With the rapid development of cellular networks, wireless base stations (WBSes) have become crucial infrastructure for mobile web systems. To ensure service quality, operators constantly monitor the operation status of WBSes and deploy anomaly detection ...

Faults are inevitable in a complex online service system. Compared with the textual incident records, the knowledge graph provides an abstract and formal representation for the empirical knowledge of how fluctuations, especially faults, propagate. ...

Log data is an essential and valuable resource of online service systems, which records detailed information of system running status and user behavior. Log anomaly detection is vital for service reliability engineering, which has been extensively ...

Anomaly detection is a crucial task for monitoring various status (i.e., metrics) of entities (e.g., manufacturing systems and Internet services), which are often characterized by multivariate time series (MTS). In practice, it's important to precisely ...

As mobile devices become more and more popular, mobile gaming has emerged as a promising market with billion-dollar revenue. A variety of mobile game platforms and services have been developed around the world. A critical challenge for these ...

Recently, considerable research attention has been paid to graph embedding, a popular approach to construct representations of vertices in latent space. Due to the curse of dimensionality and sparsity in graphical datasets, this approach has become ...

The increasing utilization of massive open online courses has significantly expanded global access to formal education. Despite the technology's promising future, student interaction on MOOCs is still a relatively under-explored and poorly understood ...

Analyzing the impact of disastrous events has been central to understanding and responding to crises. Traditionally, the assessment of disaster impact has primarily relied on the manual collection and analysis of surveys and questionnaires as well as ...

Detecting anomalous patterns from dynamic and multi-attributed network systems has been a challenging problem due to the complication of temporal dynamics and the variations reflected in multiple data sources. We propose a Multi-view Time-Series ...

This paper examines how the public perceived immigrant groups as potential risk, and how such risk perception changed after the attacks that took place in Paris on November 13, 2015. The study utilizes the Twitter conversations associated with ...

The study of disaster events and their impact in the urban space has been traditionally conducted through manual collections and analysis of surveys, questionnaires and authority documents. While there have been increasingly rich troves of human ...

Analysis of Twitter on 16 CS conferences over five years.Over time, users increase informational use and decrease conversational usage.LDA allows conference clustering, unveiling shared areas of interest.Sentiment analysis exposes differences between ...

With the allure of immediacy, social media like Twitter have been widely used in physical gatherings as a ``backchannel'' to facilitate the conversations among participants. Studies have been centered around identifying the characteristics of such ...

Twitter is often referred to as a backchannel for conferences. While the main conference takes place in a physical setting, attendees and virtual attendees socialize, introduce new ideas or broadcast information by microblogging on Twitter. In this ...

In this paper we present the latest results of a recently started project that aims at studying the extent to which links between buyers and sellers, i.e. trading interactions in online trading platforms, can be predicted from external knowledge sources ...

This paper shows a work-in-progress of a recently started project, which aims to understand how people interact with each other on Twitter during academic conferences, with emphasis on different user groups. As a first step in that direction, we ...