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Android malware poses a serious security threat to ordinary mobile users. However, the obfuscation technology can generate malware variants, which can bypass existing detection methods and significantly reduce detection accuracy. ...

• Anti-obfuscation features selection based on multi-granularity opcode features.

Influence maximization is closely related to the interesting topic of users. However, it is often ignored by most previous researches. Even though topics are considered by some previous researches, they neglect users’ different authority on ...

Logistic regression (LR) is the most commonly used loss function in multi-label image classification. However, it suffers from class imbalance problem caused by the huge difference in quantity between positive and negative samples as well as between ...

Predicting users' irregular trips in a short term period is one of the crucial tasks in the intelligent transportation system. With the prediction, the taxi requesting services, such as Didi Chuxing in China, can manage the transportation resources to ...

• Extend DPC to be able to detect overlapping communities.
• Come up with a common ...

Overlapping community detection plays an important role in studying social networks. The existing overlapping community detection methods seldom perform well on networks with complex weight distribution. Density peaks clustering (DPC) ...

Android usually employs the Secure Socket Layer (SSL) protocol to protect the user’s privacy in network transmission. However, developers may misuse SSL-related APIs, which would lead attackers to steal user’s privacy through man-in-the-middle ...

With the increasing number of microblog users, the hashtag recommendation task has become an important component in social media. Most hashtag recommendation related methods get relative low precisions, because hashtags are not necessarily related ...

Influence maximization has been widely studied in social network analysis. However, most existing works focus on user’s global influence while ignoring the fact that user’s influence varies with different topics. Even though a few works take ...

Text classification becomes a hot topic nowadays. In reality, the training data and the test data may come from different distributions, which causes the problem of domain adaptation. In this paper, we study a novel learning problem: Distant ...

The time series of stock prices are non-stationary and non-linear, making the prediction of future price trends much challenging. Inspired by Convolutional Neural Network (CNN), we make convolution on the time dimension to capture the long-term ...

Rank-integrated topic models which incorporate link structures into topic modeling through topical ranking have shown promising performance comparing to other link combined topic models. However, existing work on rank-integrated topic modeling ...

Caching is an effective optimization in search engine storage architectures. Many caching algorithms have been proposed to improve retrieval performance. The data selection policy of search engine cache management plays an important role, which ...

With the increasing adoption of role-based access control (RBAC) in business security, role mining technology has been widely applied to aid the process of migrating a non-RBAC system to an RBAC system. However, because it is hard to deal with a variety ...

With the rapid development of microblog, millions of Internet users share their opinions on different aspects of daily life. By analyzing and monitoring sentiment information extracting from tweets related to an important event, we are able to ...

Role mining was recently proposed to automatically find roles among user-permission assignments using data mining technologies. However, the current studies about role mining mainly focus on how to find roles, without considering the constraints that are ...

Caching is an effective optimization in search engine. The data selection policy plays a key role in caching, which places the data to be cached in memory. However, the current data selection policies are not suitable to the hybrid storage architecture ...

Constructing an ontology from RDBs and its query through ontologies is a fundamental problem for the development of the semantic web. This paper proposes an approach to extract ontology directly from RDB in the form of OWL/RDF triples, to ensure its ...

The progressively scale of online social network leads to the difficulty of traditional algorithms on detecting communities. We introduce an efficient and fast algorithm to detect community structure in social networks. Instead of using the eigenvectors ...

Recent research has shown that more and more web users utilize social annotations to manage and organize their interested resources. Therefore, with the growing popularity of social annotations, it is becoming more and more important to utilize such ...

Recently, there are many approaches proposed for mining roles using automated technologies. However, it lacks a tool set that can be used to aid the application of role mining approaches and update role states. In this demonstration, we introduce a tool ...