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The Research and Application of Aggregation and Generalization in Spatial Data Based on Geocoding Technique

Author: ZhangJingJing
Tutor: GuGuoQiang；LeJiaJin
School: Donghua University
Course: Computer Software and Theory
Keywords: Spatial Data ETL Address coding Levenshtein algorithm improvements Spatial data generalization
CLC: P208
Type: Master's thesis
Year: 2010
Downloads: 89
Quote: 1
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Abstract

With the development of computer technology, satellite and aerial technology matures, geographic information systems (Geographic Information System) has been widely used in various fields, increasing the proportion of spatial data types in a computer data management, how to effectively use and organizational management These spatial data to support spatial analysis and decision-making is an urgent task. Currently, the data warehouse technology has been widely used, in combination with GIS development into spatial data warehouse. Spatial data warehouse It is a powerful tool to solve this problem. Spatial data warehouse is a special form of data warehouse and its data structures on a comprehensive, integrated from different data sources according to certain topics, different types of data, can take advantage of the multi-dimensional spatial analysis methods, from different angles, hidden space Comprehensive analysis and comparison of the information and attribute data in order to achieve the purpose of data mining. The study of the spatial data warehouse is a current hot topic. This paper focuses on the spatial data warehouse building in the following basic work carried out a preliminary study: The first is based on the address coding spatial data aggregation. The first step is to build a spatial data warehouse to standardize data formats directly affect the effectiveness of the system, because the quality of the data. Address coding is a method of polymerization heterogeneous spatial data sources. Complexity of Chinese characters has a long local history of cultural connotations address, far more than in other countries, therefore, the foreign coding standard is not suitable for use. In this paper, based on the analysis of a variety of address feature, comprehensive MIS semantic address classification and GIS the geometric spatial data classification concepts strengths, and put forward a new address, coding method, the use of this method to build a data model to more effectively achieve space data aggregation. Followed by the generalization of spatial data. Generalization largely of heterogeneous, multi-source spatial data can be converted to the data similarity distance, similarity calculation method is based on the generalization of the standard address data semantics address the key technologies, this paper analyzes the Levenshtein algorithm used , the jurisdictions address does not match the question Levenshtein algorithm improved reverse match the address details of the address data often combined with the practical application of project; Levenshtein edit distance problem for the same semantic address the homonym different word phonetic code improved replacement algorithm, to improve the accuracy of address match. On the basis of research and experimental validation of the above two issues, this results to \Similarity algorithm proposed in this paper to address coding of space-based data aggregation and generalization of certain guiding significance and practical value of similar problems.

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