In this paper, we address the problem of data Compression which is critical in wireless sensor networks. We proposed a novel Topology-based data Compression (TDC) algorithm for wireless sensor networks. We utilize the...
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Consumer online shopping behaviors are well attended in the IS and marketing literature. Yet, there is another group of individuals who spend a lot of time online but do not purchase anything. This online window shopp...
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Consumer online shopping behaviors are well attended in the IS and marketing literature. Yet, there is another group of individuals who spend a lot of time online but do not purchase anything. This online window shopping phenomenon is intriguing to both scholars and marketers yet it is less studied and little understood. Questions such as what the online window shopping consumers do during their visits, how to differentiate their activities and how to design marketing strategies to stimulate them to buy are all essential and beg for investigation. To address this gap, we propose a typology of online window shopping consumers based on the Consumer Information Processing Model, then empirically validate and refine the typology using a set of clickstream data. The final typology contains four main types of online window shopper consumers: 1) promotion finders, 2) social & hedonic experience seekers, 3) information gatherers, and 4) learners & novices. This study extends consumer online behavior research in both e-commerce and social commerce by focusing on the specific group of consumers who only do online window shopping. Besides theoretical contributions, the findings also provide marketers and businesses with valuable references for designing targeted marketing strategies or promotional activities for online window shopping consumers.
Along with the development of Internet and Web2.0, online social networks (OSNs) are becoming an important information propagation platform. Therefore, it is of great significance to study the information propagation ...
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In this paper, the author defines Generalized Unique Game Problem (GUGP), where weights of the edges are allowed to be negative. Two special types of GUGP are illuminated, GUGP-NWA, where the weights of all edges are ...
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As the sharable and reusable domain knowledge, domain ontology increasingly serves as a foundation for semantic Web. Personalized management of domain ontologies is to provide personalized views of domain ontologies t...
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As the sharable and reusable domain knowledge, domain ontology increasingly serves as a foundation for semantic Web. Personalized management of domain ontologies is to provide personalized views of domain ontologies to users during run time according to user preferences. It helps that users can focus on their interested parts, instead of the whole. It increases the efficiency of ontology-based application. This paper proposes a framework for personalized management of domain ontologies. In this framework, a user model firstly is introduced to describe user preferences. Secondly, domain ontologies are decomposed into moderate-scale modules with high cohesion and low coupling. During run time, modules that a user is interested in are selected out based on the user's preferences. Finally, the selected modules are combined to construct personalized views of domain ontologies for the user.
A novel method is proposed to automatically extract foreground objects from Martian surface *** characteristics of Mars images are distinct,*** illumination,low contrast between foreground and background,much noise in...
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A novel method is proposed to automatically extract foreground objects from Martian surface *** characteristics of Mars images are distinct,*** illumination,low contrast between foreground and background,much noise in the background,and foreground objects with irregular *** the context of these characteristics,an image is divided into foreground objects and background *** filtering is first applied to rectify ***,wavelet transformation enhances contrast and denoises the ***,edge detection and active contour are combined to extract contours regardless of the shape of the *** results show that the method can extract foreground objects from Mars images automatically and accurately,and has many potential applications.
Given a multi-features data set, a best preference query (BPQ) computes the maximal preference score (MPS) that the tuples in the data set can achieve with respect to a preference function. BPQs are very useful in app...
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This paper proposes a two-fold study: (1) to find the factors affecting attitude of Thai students for choosing Information Technology (IT) program and (2) to investigate the existence of gender gap in behavioral inten...
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This paper proposes a two-fold study: (1) to find the factors affecting attitude of Thai students for choosing Information Technology (IT) program and (2) to investigate the existence of gender gap in behavioral intention. The study is based on the Theory of Reasoned Action (TRA) as a theoretical framework. The factors that may affect students’ behavioral intention to choose IT program are categorized into two dimensions: attitudes toward choosing IT program and subjective norm. The web-based questionnaire is employed to collect data from a sample of 67 local Thai Grade 12 students of both genders who have intention to study in IT undergraduate program at School of Information Technology (SIT), King Mongkut's University of Technology Thonburi (KMUTT). The result of statistical analysis shows that TRA is effective for explaining the behavioral intention. Male and female students hold the same set of attitudinal attributes when deciding to enter IT program, hence, an IT school shall implement common strategies to grasp intention from both genders. The most effective strategy to gain students intention is to build up the reputation of IT program.
In this paper, we study how to perform XML query expansion effectively from the high quality pseudo-relevance documents. A solution for selecting good expansion information is presented, in which various features impa...
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In this paper, we study how to perform XML query expansion effectively from the high quality pseudo-relevance documents. A solution for selecting good expansion information is presented, in which various features impacting weight, such as term element frequency, term inverse element frequency, semantic weight of tag and level information, are analyzed and those term with high weigh value are selected as expansion term. Experiment results show that proposed expansion method is feasible. Compared to original query and traditional expansion method with no structure features considered, our method achieves better retrieval performance.
Currently, most works on interval valued problems mainly focus on attribute reduction (i.e., feature selection) by using rough set technologies. However, less research work on classifier building on interval-valued pr...
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Currently, most works on interval valued problems mainly focus on attribute reduction (i.e., feature selection) by using rough set technologies. However, less research work on classifier building on interval-valued problems has been conducted. It is promising to propose an approach to build classifier for interval-valued problems. In this paper, we propose a classification approach based on interval valued fuzzy rough sets. First, the concept of interval valued fuzzy granules are proposed, which is the crucial notion to build the reduction framework for the interval-valued databases. Second, the idea to keep the critical value invariant before and after reduction is selected. Third, the structure of reduction rule is completely studied by using the discernibility vector approach. After the description of rule inference system, a set of rules covering all the objects can be obtained, which is used as a rule based classifier for future classification. Finally, numerical examples are presented to illustrate feasibility and affectivity of the proposed method in the application of privacy protection.
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