کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4965319 1448278 2017 29 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A feature selection approach towards progressive vector transmission over the Internet
ترجمه فارسی عنوان
رویکرد انتخاب ویژگی به انتقال بردار مترقی از طریق اینترنت
کلمات کلیدی
انتقال پیشرفته، انتخاب ویژگی، مقدار اطلاعات، پروتکل انتقال واقعی در زمان واقعی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
WebGIS has been applied for visualizing and sharing geospatial information popularly over the Internet. In order to improve the efficiency of the client applications, the web-based progressive vector transmission approach is proposed. Important features should be selected and transferred firstly, and the methods for measuring the importance of features should be further considered in the progressive transmission. However, studies on progressive transmission for large-volume vector data have mostly focused on map generalization in the field of cartography, but rarely discussed on the selection of geographic features quantitatively. This paper applies information theory for measuring the feature importance of vector maps. A measurement model for the amount of information of vector features is defined based upon the amount of information for dealing with feature selection issues. The measurement model involves geometry factor, spatial distribution factor and thematic attribute factor. Moreover, a real-time transport protocol (RTP)-based progressive transmission method is then presented to improve the transmission of vector data. To clearly demonstrate the essential methodology and key techniques, a prototype for web-based progressive vector transmission is presented, and an experiment of progressive selection and transmission for vector features is conducted. The experimental results indicate that our approach clearly improves the performance and end-user experience of delivering and manipulating large vector data over the Internet.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Geosciences - Volume 106, September 2017, Pages 150-163
نویسندگان
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