In recent years, auction theory has been extensively studied and many state-of-the-art solutions have been proposed aiming at allocating scarce resources. However, most of these studies assume that the auctioneer is always trustworthy in the sealed-bid auctions, which is not always true in a more realistic scenario. Besides the privacy-preserving issue, the performance guarantee of social efficiency maximization is also crucial for auction mechanism design. In this paper, we study the auction...

Hashtags are important metadata in microblogs and are used to mark topics or index messages. However, statistics show that hashtags are absent from most microblogs. This poses great challenges for the retrieval and analysis of these tagless microblogs. In this paper, we summarize the similarity between microblogs and short-message-style news, and then propose an algorithm, named 5WTAG, for detecting microblog topics based on a model of five Ws (When, Where, Who, What, hoW). As five-W attribut...

With cloud computing technology becoming more mature, it is essential to combine the big data processing tool Hadoop with the Infrastructure as a Service (IaaS) cloud platform. In this study, we first propose a new Dynamic Hadoop Cluster on IaaS (DHCI) architecture, which includes four key modules: monitoring, scheduling, Virtual Machine (VM) management, and VM migration modules. The load of both physical hosts and VMs is collected by the monitoring module and can be used to design resource s...

The Extreme Learning Machine (ELM) and its variants are effective in many machine learning applications such as Imbalanced Learning (IL) or Big Data (BD) learning. However, they are unable to solve both imbalanced and large-volume data learning problems. This study addresses the IL problem in BD applications. The Distributed and Weighted ELM (DW-ELM) algorithm is proposed, which is based on the MapReduce framework. To confirm the feasibility of parallel computation, first, the fact that matri...

In this paper, we target a similarity search among data supply chains, which plays an essential role in optimizing the supply chain and extending its value. This problem is very challenging for application-oriented data supply chains because the high complexity of the data supply chain makes the computation of similarity extremely complex and inefficient. In this paper, we propose a feature space representation model based on key points, which can extract the key features from the subsequence...

Knowledge graph representation has been a long standing goal of artificial intelligence. In this paper, we consider a method for knowledge graph embedding of hyper-relational data, which are commonly found in knowledge graphs. Previous models such as Trans (E, H, R) and CTransR are either insufficient for embedding hyper-relational data or focus on projecting an entity into multiple embeddings, which might not be effective for generalization nor accurately reflect real knowledge. To overcome ...

In this paper, we analyze the video steganography technique, which is used to ensure national security and the confidentiality of the information of governmental agencies and enterprises. Videos may be used to transmit secrets and conduct covert communication. As such, we present an algorithm based on a secret sharing scheme and an Error-Correcting Code (ECC), which combines Grey Relational Analysis (GRA) with a partition mode in video compression standard H.264/AVC. First, we process secret ...

Instance-specific algorithm selection technologies have been successfully used in many research fields, such as constraint satisfaction and planning. Researchers have been increasingly trying to model the potential relations between different candidate algorithms for the algorithm selection. In this study, we propose an instance-specific algorithm selection method based on multi-output learning, which can manage these relations more directly. Three kinds of multi-output learning methods are u...

In TrustZone architecture, the Trusted Application (TA) in the secure world does not certify the identity of Client Applications (CA) in the normal world that request data access, which represents a user data leakage risk. This paper proposes a private user data protection mechanism in TrustZone to avoid such risks. We add corresponding modules to both the secure world and the normal world and authenticate the identity of CA to prevent illegal access to private user data. Then we analyze the ...