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Article
HAN-CAD: hierarchical attention network for context anomaly detection in multivariate time series
Anomaly Detection in multivariate time series (MTS) plays an important role in many real-world Web services such as the Web traffic monitoring system. With abundant MTS data, exploiting the relationships among...
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Article
Graph convolutional network with multi-similarity attribute matrices fusion for node classification
Graph convolution networks (GCNs) have become one of the most popular deep neural network-based models in many real-world applications. GCNs can extract features take advantage of both graph structure and node...
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Article
Intra- and inter-association attention network-enhanced policy learning for social group recommendation
Social Group Recommendation (SGR) is a critical task to recommend items to a group of users in social network platforms, such as Meetup, Douban, Mofengwo, etc. Recently, many state-of-the-art works have addres...
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Chapter and Conference Paper
Supervised Prototypical Variational Autoencoder for Shilling Attack Detection in Recommender Systems
Collaborative filtering-based recommender systems are vulnerable to shilling attacks. How to detect shilling attacks has become a popular research direction. Some recent works have applied deep learning to the...
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Article
Attentive multi-task learning for group itinerary recommendation
Tourism is one of the largest service industries and a popular leisure activity participated by people with friends or family. A significant problem faced by the tourists is how to plan sequences of points of ...
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Article
GLEAM: a graph clustering framework based on potential game optimization for large-scale social networks
With the growing explosion of online social networks, the study of large-scale graph clustering has attracted considerable interest. Most of traditional methods view the graph clustering problem as an optimiza...
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Reference Work Entry In depth
Models for Community Dynamics
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Book
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Chapter
Ad Fraud Measure and Benchmark
In this chapter, we discuss measures and benchmark datasets commonly used for Ad fraud detection. The measures include fraud detection accuracy, precision, recall, F-measure, and AUC scores which are commonly ...
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Chapter
Conclusion
Online advertising fraud represents a significant portion of deceiving actions in digital advertising systems which use numerous technologies to derive illicit returns. Even the most conservative estimation ha...
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Chapter
Ad Ecosystems and Key Components
In this chapter, we briefly describe the digital advertising ecosystem, mainly from the display advertising perspective. We will first describe the real-time bidding framework for online digital advertising, i...
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Chapter
Ad Fraud Detection Tools and Systems
This chapter reviews both commercial Ad fraud detection and prevention systems and the ones developed in academia. For commercial systems, they mainly emphasize on the efficiency, so fraud detection can be ach...
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Chapter
Introduction
In this chapter, we briefly introduce the computational advertising, including search advertising and display advertising. We explain the reality of fraud in digital advertising, and summarize types of fraud m...
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Chapter
Ad Fraud Taxonomy and Prevention Mechanisms
In this chapter, we first propose a taxonomy to summarize fraud in online digital advertising. The taxonomy provides a complete view of major fraudulent activities in answering questions related to Who does Wh...
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Chapter
Ad Fraud Categorization and Detection Methods
This chapter provides a comprehensive review of Ad fraud in three major categories: placement fraud, traffic fraud, and action fraud, which are at different levels of online advertising. Placement fraud mainly...
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Living Reference Work Entry In depth
Models for Community Dynamics
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Chapter and Conference Paper
Understanding User Behavior through URL Analysis in Sina Tweets
As the popularity of online social networks, the user behavior in cyber-world might probably become a mirror of the user in physical world. Therefore, understanding online user’s behavior is an interesting yet...
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Reference Work Entry In depth
Models for Community Dynamics
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Chapter and Conference Paper
A Cloud System for Community Extraction from Super-Large Scale Social Networks
This demo showcase the Community Extraction Cloud (CEC) system. The key idea is to drop weak-tie nodes by efficiently extracting core nodes based on the novel concept of asymptotically equivalent structures (A...
