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While e-commerce has grown substantially over last several years, more and more people are utilizing this popular channel to purchase products and services. Thus the ability to predict user demographics, including gender, age and location has important applications in advertising, personalization, and recommendation. In this paper, we aim to automatically predict the users' genders based on their...
In order to improve the discriminant power, a new discriminant analysis algorithm is proposed based on Fisher's linear discriminant, called variant fisher discriminant analysis with orthogonal discriminant components (VFDAODC). The basic idea of the proposed VFDAODC is to overcome the problems of the conventional fisher discriminant analysis algorithm. First, a two-step feature extraction procedure...
We present a novel hierarchical MRFs optimization method for dense and deformable motion extraction in dynamic scenes. In particular, this hierarchical MRFs structure consists of two layers, the segmentation and the correspondence layer. Firstly, dynamic RGB-D foreground data is segmented through a pixel-level MRF in the segmentation layer. Subsequently, the extracted foreground data is transformed...
In current days, data tend to become much bigger than before, and the distributed computing system is an prevalent option to deal with them. As one of powerful tools, MapReduce framework provides a cheap and efficient way to write parallel programs to run on distributed computing systems. Chance discovery (CD) is an extension of data mining, where chance refers to rare but important events or situations...
An approach for keyframe extraction using AdaBoost is proposed which is based on foreground detection. The aim of this approach is to extract keyframes from sequences of specific vehicle images of lane vehicle surveillance video. This method utilizes integral channel features and the area feature as the image feature descriptor, combined with training an AdaBoost classifier. The experimental results...
The problem of efficiently finding top-k frequent items has attracted much attention in recent yeras. Storage constraints in the processing node and intrinsic evloving feature of the data streams are two main challenges. In this paper, we propose a method to tackle these two challenges based on space-saving and gossip-based algorithms respectively. Our method is implemented on SAMOA, a scalable advanced...
Extracting main object from photos is prerequisite for image processing and semantic image understanding in many areas especially in multimedia signal processing at internet. So far, either human interaction in single image or sequence image frames are required for the extraction and most of them still rely on hand-crafted features. In contrast, the proposed work cast the human boundary detection...
Big data analytics is the process of examining large amounts of data of a variety of types (big data) to uncover hidden patterns, unknown correlations and other useful information. Its revolutionary potential is now universally recognized. Data complexity, heterogeneity, scale, and timeliness make data analysis a clear bottleneck in many biomedical applications, due to the complexity of the patterns...
Based on data mining, the main impact factors of urban life water consumption are made gray relational analysis with the water consumption. The main driving factors of urban life water consumption are discussed. By the gray forecasting of the development trends of the main impact factors, a grey prediction of GM (0, N) model on urban life water is established. An instance proves to fit the data better...
Classification of high frequency micro logs has been completed. A model is proposed in which the direct influence is based on some factors: the micro logger's aggregation, the activity, the amount of microblog comments and the number of fans, and the indirect influence is based on the forward depth and repost time. Official microblog "Chongqing Mobile" and grassroots microblog "Hong...
Wind power short-term prediction method generally depends on the meteorological data at present. This paper proposed time series power prediction method which is based on multi-scale tuple matching and can predict wind power well by making full use of historical data without affecting the computational efficiency to predict wind power on the occasion where power series can be obtained but the meteorological...
The Mining Software Repositories (MSR) research community has grown significantly since the first MSR workshop was held in 2004. As the community continues to broaden its scope and deepens its expertise, it is worthwhile to reflect on the best practices that our community has developed over the past decade of research. We identify these best practices by surveying past MSR conferences and workshops...
Software frameworks provide sets of generic functionalities that can be later customized for a specific task. When developers invoke API methods in a framework, they often encounter obstacles in finding the correct usage of the API, let alone to employ best practices. Previous research addresses this line of questions by mining API usage patterns to induce API usage templates, by conducting and compiling...
In Internet Certification Service (ICS), we use the content associated sensitive data extraction technology to increase the security of High Definition video copyright for ICS disc. An important item of ICS is to evaluate the Video Destruction Level (VDL) after extracting sensitive data. This paper presents a flexible and easy simulation environment to calculate the VDL based on DirectShow and Matlab.
Service management is becoming more and more important within the area of IT management. How to efficiently manage and organize service in complicated IT service environments with frequent changes is a challenging issue. IT service and the related information from different sources are characterized as diverse, incomplete, heterogeneous, and geographically distributed. It is hard to consume these...
In this paper, the framework of MapReduce is explored for large-scale multimedia data mining. Firstly, a brief overview of MapReduce and Hadoop is presented to speed up large-scale multimedia data mining. Then, the high-level theory and low-level implementation for several key computer vision technologies involved in this work are introduced, such as 2D/3D interest point detection, clustering, bag...
This paper proposes an information hiding scheme based on the Context-based Adaptive Variable Length Coding (CAVLC) mode of entropy encoding in H.264/AVC video encoding standard. The scheme hides information in the process of encoding the trailing coefficient in CAVLC, just in luminance (luma) components of 4x4 DCT data blocks. By modifying the check sum of codeword encoded for the trailing coefficient...
Framework-based1 applications are quite popularly used in current commercial applications. Framework-based applications are often controlled by XML configuration files. However, most of these frameworks are complex or not well documented, which poses a great challenge for programmers to correctly utilize them. To overcome these difficulties, we propose a new method to recommend XML configuration snippets...
How to deploy commodities for sale in different shelves in a supermarket in order to obtain better benefit for merchants with considering convenience for customers is an important topic in the retail area. In this paper, we present a new method for allocating commodity shelves in supermarket based on customers' shopping paths and transactions data mining. Therein, customers' shopping paths data can...
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