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With the market competition being increasingly intensive, it is necessary for company to carry out one-to-one marketing to consumers. Therefore, the ability to predict consumer's consumption behavior basing on data mining has become a key source of competitive advantage for company. In this paper, we propose a novel algorithm, which bases on ant colony optimization (ACO) to cluster consumer's consumption...
With the rapid development of online shopping, electronic commerce has offered a new channel for instant on-line shopping. It is necessary for company to on-line one-to-one market to e-shoppers. Therefore, the ability to predict e-shoppers' purchase behavior basing on data mining has become a key source of competitive advantage for company. Frequently occurring sequential patterns, identified in sequences...
Manifold learning is an emerging and promising approach in nonlinear dimension reduction. Representative methods include locally linear embedding (LLE) and Isomap. However, both methods fail to guarantee connectedness of the constructed neighborhood graphs. We propose k variable method called kv-LLE and kv-Isomap to build connected neighborhood graphs so as to enhance the robustness. The applicability...
Digital watermarking is an efficient and promising approach to protect intellectual property rights of digital media. In this paper, a new scheme of robust audio watermarking based on Fractional Fourier transform (FRFT) domain for copyright protection is proposed, which utilizes the idea that FRFT can be considered as a rotation in time-frequency joint domain. Test results for imperceptibility of...
By virtue of lower price, smaller size and lighter weight than that of traditional rate sensors, the Micro-Electro-Mechanical System (MEMS) has been widely developed to use in low cost and miniaturized Inertia! Measurement Units (IMU). However, the MEMS gyroscopes usually have large drift, which limit its use. In this paper, a one-order autoregressive (AR) model is built for the residual signal of...
The present algorithms for artificial neural network, to a certain extent, have various questions such as computational complexity, low accuracy and narrow scope of application. This paper presents a new algorithm for extracting accurate and comprehensible rules from databases via trained artificial neural network using genetic algorithm. The new algorithm does not depend on the ANN training algorithms;...
We are exploring a novel information theory based approach to analyse the relation of the number of protein interactions (interaction perplexity) and protein function. The interaction perplexity is translated into a smooth sigmoid function, indicating if the protein is a hub candidate or not (hub likelihood). The overall mutual information between the hub likelihood and the protein function exhibits...
In the Internet shopping environment, changes of customer's needs grow increasingly outstanding. For discovering the changes, the paper mines the transaction databases of different time periods by using association rule discovery, and extracts the association rules and discovers the changes in network customer behavior by comparison and analysis between the two sets of association rules. This paper...
Agent based programming has been described as the next significant breakthrough in software development, and it has been used for building intelligent agents. The agent-oriented approach is increasingly being applied in industrial applications, but it is far from as widespread as the object-oriented approach. Also the paper describes where and how agents have been applied to the manufacturing industry...
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