This paper attempts to use soft information in finance to rank the risk levels of a set of companies. Specifically, we deal with a ranking problem with a collection of financial reports, in which each report is associ...
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This paper proposes a context-aware approach that recommends music to a user based on the user's emotional state predicted from the article the user writes. We analyze the association between user-generated text a...
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This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of informati...
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This paper proposes a music recommendation approach based on various similarity information via Factorization Machines (FM). We introduce the idea of similarity, which has been widely studied in the filed of information retrieval, and incorporate multiple feature similarities into the FM framework, including content-based and context-based similarities. The similarity information not only captures the similar patterns from the referred objects, but enhances the convergence speed and accuracy of FM. In addition, in order to avoid the noise within large similarity of features, we also adopt the grouping FM as an extended method to model the problem. In our experiments, a music-recommendation dataset is used to assess the performance of the proposed approach. The datasets is collected from an online blogging Web site, which includes user listening history, user profiles, social information, and music information. Our experimental results show that, with various types of feature similarities the performance of music recommendation can be enhanced significantly. Furthermore, via the grouping technique, the performance can be improved significantly in terms of Mean Average Precision, compared to the traditional collaborative filtering approach.
It is well known that the photo-interpretation of radar images is substantially different from the optical images due to SAR's scattering mechanism. Merging optical images with SAR imagery can provide complementar...
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It is well known that the photo-interpretation of radar images is substantially different from the optical images due to SAR's scattering mechanism. Merging optical images with SAR imagery can provide complementary information in order to improve understanding the structure of the features within the SAR. To achieve the goal, this research has developed an extension model of the IHS-BT approach (eIHS-BT) with multi-optional adjustments for image fusion. The model provides four fusion methods of Pan-MS, SAR-MS, SAR-Pan-MS and SAR-Pan by setting two parameters. Apart from that, the SAR-Pan-MS or SAR-Pan image fusion method can show better performance in assisting SAR image understanding because of reasonable contents of spatial details and texture features by tuning one parameter for adjusting the proportion of Pan to SAR image information. In the mean time, an effectively red-green viewer (RGV) to increase the quality of the radar images is introduced to assist object recognition by reducing the bright star effect.
Behavior, including non verbal, expressiveness is an integral part of the communication process since it can provide information on the emotional state and the user's performance when the aim of the interaction is...
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A bipartite graph is bipanconnected if an arbitrary pair of vertices x, y are joined by the bipanconnected paths that include a path of each length s satisfying N - 1 ≥ s ≥dist(x, y) and i - dist(x, y) is even, wher...
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In this paper, we conducted an user study on digital magazine applications based on three different interaction styles. Though different reading interfaces and applications of mobile device to focused on the reading b...
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Information Retrieval (IR) aims to discover relevant information according to a user's information need. The classic Probability Ranking Principle (PRP) forms the theoretical basis for probabilistic IR models. Thi...
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Information Retrieval (IR) aims to discover relevant information according to a user's information need. The classic Probability Ranking Principle (PRP) forms the theoretical basis for probabilistic IR models. This ranking principle, however, neglects the uncertainty introduced through the estimations from retrieval models. Inspired by the Post-Modern Portfolio Theory (PMPT), this paper proposes a mean-semivariance framework to handle the uncertainty. The proposed framework not only deals with the uncertainty but has the ability to distinguish bad surprises (downside uncertainty) and good surprises (upside uncertainty) when optimizing a ranking list. The experimental results shows that the proposed method improves the IR performance over the PRP baseline in terms of most of IR evaluation metrics; moreover, the results suggest that the mean-semivariance framework can further boost the top-position ranking quality.
The goal of our research is to develop a computer system based on the concept of pictures-And-Attributed-notes (PAN) aiming to stimulate creativity and imagination when users create a story. We have conducted an exper...
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ISBN:
(纸本)9781450308205
The goal of our research is to develop a computer system based on the concept of pictures-And-Attributed-notes (PAN) aiming to stimulate creativity and imagination when users create a story. We have conducted an experiment and used the Conceptual, Operational, Perceptional and Evaluation (COPE) coding system to analyze the process of creating a story with the aid of computer system. The preliminary results revealed that the computer system based on PAN can stimulate user's creativity during the process of story creation. Copyright 2011 ACM.
In this study, we implemented a digital game-based learning (DGBL) system over Face book platform. For better understanding the impact of DGBL applied to social networking, the technology acceptance model (TAM) was em...
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In this study, we implemented a digital game-based learning (DGBL) system over Face book platform. For better understanding the impact of DGBL applied to social networking, the technology acceptance model (TAM) was employed for the evaluation. Results of this study showed that the DGBL incorporated into a social network website is a feasible and sound model for teaching. This study investigated the potential important design issues of the application over a social network website. It is believed that this study could bring teachers a better understanding how those characteristics of social networks can attribute to the success of users' learning.
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