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RISS 인기검색어
- 검색키워드
- 저자 : Chiu-I Hsu (검색결과 3 건)
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- 유료
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Efficiently Processing Skyline Query on Multi-Instance Data
Chiu, Shu-I,Hsu, Kuo-Wei Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.5
Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples, where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to the beach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in all dimensions and better in at least one dimension. Traditionally, skyline queries are defined upon single-instance data or upon objects each of which is associated with an instance. However, in some cases, an object is not associated with a single instance but rather by multiple instances. For example, on a review website, many users assign scores to a product or a service, and a user's score is an instance of the object representing the product or the service. Such data is an example of multi-instance data. Unlike most (if not all) others considering the traditional setting, we consider skyline queries defined upon multi-instance data. We define the dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic and real data to evaluate the proposed methods, and the results demonstrate their utility.
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Efficiently Processing Skyline Query on Multi-Instance Data
Shu-I Chiu,Kuo-Wei Hsu 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.5
Related to the maximum vector problem, a skyline query is to discover dominating tuples from a set of tuples,where each defines an object (such as a hotel) in several dimensions (such as the price and the distance to thebeach). A tuple, an instance of an object, dominates another tuple if it is equally good or better in alldimensions and better in at least one dimension. Traditionally, skyline queries are defined upon singleinstancedata or upon objects each of which is associated with an instance. However, in some cases, an objectis not associated with a single instance but rather by multiple instances. For example, on a review website,many users assign scores to a product or a service, and a user’s score is an instance of the object representingthe product or the service. Such data is an example of multi-instance data. Unlike most (if not all) othersconsidering the traditional setting, we consider skyline queries defined upon multi-instance data. We definethe dominance calculation and propose an algorithm to reduce its computational cost. We use synthetic andreal data to evaluate the proposed methods, and the results demonstrate their utility.
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College student perceptions about the incorporation of cultural elements in fashion design
Hui-Yun Yen,Chiu-I Hsu 한국의류학회 2017 Fashion and Textiles Vol.4 No.1
The cultural and creative industries have received considerable global attention in recent years; in particular, the close relationship between these industries and design has been identified. Because mysterious and attractive East Asian aesthetic are a crucial contemporary style, this study examined a fashion exhibition held in the New York Metropolitan Museum, which entitled “China: Through the Looking Glass” and conducted a literature review, scale design, survey and data analysis, and factor analysis about the incorporation of cultural elements in fashion design. Subsequently, the perceptions of college students with various educational backgrounds on several selected exhibits were identified and analyzed. The results were revealed that: (1) the research scale can be used as a reference for related design teaching and in the appraisal of fashion products in the design industry; (2) cultural connotations are more notable in design than the technical aspects; (3) compared with students of other backgrounds, students with a background in fashion design emphasized more on the technical and professional aspects and expressed a preference for design pieces with experimental qualities, such as those made with stiff materials and having exaggerated styles, and neutral and neat straight lines.
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