228 citations · 813 across the 67 of their papers we have counts for
13 papers · 1 filter
On the Detection of Reviewer-Author Collusion Rings From Paper Bidding
Steven Jecmen, Nihar B. Shah, Fei Fang +1
A major threat to the peer-review systems of computer science conferences is the existence of "collusion rings" between reviewers. In such collusion rings, reviewers who have also…
Summarizing Labeled Multi-Graphs
Dimitris Berberidis, Pierre J. Liang, Leman Akoglu
Real-world graphs can be difficult to interpret and visualize beyond a certain size. To address this issue, graph summarization aims to simplify and shrink a graph, while maintaini…
Detecting Changed-Hands Online Review Accounts
Geli Fei, Shuai Wang, Bing Liu +1
A reputable social media or review account can be a good cover for spamming activities. It has become prevalent that spammers buy/sell such accounts openly on the Web. We call thes…
AutoAudit: Mining Accounting and Time-Evolving Graphs
Meng-Chieh Lee, Yue Zhao, Aluna Wang +4
How can we spot money laundering in large-scale graph-like accounting datasets? How to identify the most suspicious period in a time-evolving accounting graph? What kind of account…
LookOut on Time-Evolving Graphs: Succinctly Explaining Anomalies from Any Detector
Nikhil Gupta, Dhivya Eswaran, Neil Shah +2
Why is a given node in a time-evolving graph (-graph) marked as an anomaly by an off-the-shelf detection algorithm? Is it because of the number of its outgoing or incoming edges…
Fast, Warped Graph Embedding: Unifying Framework and One-Click Algorithm
Siheng Chen, Sufeng Niu, Leman Akoglu +2
What is the best way to describe a user in a social network with just a few numbers? Mathematically, this is equivalent to assigning a vector representation to each node in a graph…
Ties That Bind - Characterizing Classes by Attributes and Social Ties
Aria Rezaei, Bryan Perozzi, Leman Akoglu
Given a set of attributed subgraphs known to be from different classes, how can we discover their differences? There are many cases where collections of subgraphs may be contrasted…
Temporal Opinion Spam Detection by Multivariate Indicative Signals
Junting Ye, Santhosh Kumar, Leman Akoglu
Online consumer reviews reflect the testimonials of real people, unlike advertisements. As such, they have critical impact on potential consumers, and indirectly on businesses. Acc…
Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs
Emaad A. Manzoor, Sadegh Momeni, Venkat N. Venkatakrishnan +1
Given a stream of heterogeneous graphs containing different types of nodes and edges, how can we spot anomalous ones in real-time while consuming bounded memory? This problem is mo…
Scalable Anomaly Ranking of Attributed Neighborhoods
Bryan Perozzi, Leman Akoglu
Given a graph with node attributes, what neighborhoods are anomalous? To answer this question, one needs a quality score that utilizes both structure and attributes. Popular existi…
EdgeCentric: Anomaly Detection in Edge-Attributed Networks
Neil Shah, Alex Beutel, Bryan Hooi +5
Given a network with attributed edges, how can we identify anomalous behavior? Networks with edge attributes are commonplace in the real world. For example, edges in e-commerce net…
Where Graph Topology Matters: The Robust Subgraph Problem
Hau Chan, Shuchu Han, Leman Akoglu
Robustness is a critical measure of the resilience of large networked systems, such as transportation and communication networks. Most prior works focus on the global robustness of…
Graph-based Anomaly Detection and Description: A Survey
Leman Akoglu, Hanghang Tong, Danai Koutra
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. While numerous techniques…