Urban functional area identification process based on space-time semantic mining

Abstract

The invention discloses an urban functional area identification process based on space-time semantic mining, which comprises documents, words, basic functional units, space-time data, a topic model, document topic distribution and unit function distribution, and is characterized in that firstly, hidden functions of an area are tried to discover through the topic model, compared with a text theme mining, the basic function units are equivalent to the documents in a corpus, space-time data in the basic function unit is similar to words in the document, unit function distribution obtained after passing through the topic model is equivalent to document topic distribution, and the used city space-time data is representative Sina microblog position sign-in data. Each piece of sign-in data comprises user information, space coordinates of sign-in positions, publishing time, publishing texts and the like. Dynamic activity modes of people can be reflected from different angles, meanwhile, POIs in a research area are obtained from a Baidu map, and function recognition of the area is achieved.

Description

technical field [0001] The invention relates to the technical field of urban functional area identification, in particular to an urban functional area identification process based on spatio-temporal semantic mining. Background technique [0002] Traditional urban functional zoning studies are mostly based on data obtained from satellite remote sensing, questionnaire surveys, and field visits, supplemented by index systems to identify urban functional areas [1-3], but these methods consume too much labor cost, Moreover, there are subjective factors of investigators in the analysis process, which makes it difficult to accurately conduct long-term dynamic monitoring of urban functional areas. Contents of the invention [0003] The object of the present invention is to provide a high-performance anti-oxidation polyethylene plastic to solve the problems raised in the above-mentioned background technology. [0004] In order to achieve the above object, the present invention pro...

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Problems solved by technology

[0002] Most of the traditional urban functional zoning studies are based on data obtained from satellite remote sensing, questionnaire surveys, and field visits, supplemented by an index system for the identification of urban functional areas [1-3]. However, these methods consume too much labor cost. In addition, there are subjective factors of investigators in the analysis process, making it difficult to accurately conduct long-term dynamic monitoring of urban functional areas

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