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In this paper, an approach for reorganizing Web sites based on user access patterns is proposed. The approach consists of three steps: preprocessing, page classification, and site reorganization. In preprocessing, pages on a Web site are processed to create an internal representation of the site, and page access information of its users is extracted from(More)
Previous studies have shown that website design elements (such as text and pictures) can be manipulated to increase the perception of Social Presence (SP) among online consumers, which can then impact trust, usefulness and enjoyment. This paper seeks to determine if the impacts of infusing SP in websites is culture specific or universal. We were able to(More)
In this paper, we propose a new unsupervised spectral feature selection model by embedding a graph regularizer into the framework of joint sparse regression for preserving the local structures of data. To do this, we first extract the bases of training data by previous dictionary learning methods and, then, map original data into the basis space to generate(More)
Although there are many good collaborative recommendation methods, it is still a challenge to increase the accuracy and diversity of these methods to fulfill users' preferences. In this paper, we propose a novel collaborative filtering recommendation approach based on K-means clustering algorithm. In the process of clustering, we use artificial bee colony(More)
Emotion is an important aspect of human intelligence and has been shown to play a significant role in the human decision-making process. This paper proposes a comprehensive computational model of emotions that can be incorporated into the physiological and social components of the emotions. Since interaction between characters can have a major impact on(More)
To deal with credit card fraud, a detection model based on Class Weighted Support Vector Machine was established. Due to large-scale and high dimensions of data, Principal Component Analysis (PCA) was adopted firstly to screen out the main factors from a great deal of indicative attributes in order to reduce the training dimension of SVM effectively. Then(More)
This article addresses a multi-query optimization problem for distributed medical image retrieval in mobile wireless networks by exploiting the dependencies in the derivation of a retrieval evaluation plan. To the best of our knowledge, this is the first work investigating batch medical image retrieval (BMIR) processing in a mobile wireless network(More)
AI (artificial intelligence) techniques, especially neural network, have been used widely for business forecasting. There are so many factors affecting the business forecasting that the input nodes number is large. Conventional neural network methods suffer from limitations, which make them less than adequate for decision making in dynamic business(More)