关键词: 地理编码, 实时流处理, 地理大数据, Storm

Abstract:

The explosion in geographical data with spatio-temporal characteristics has led a surge in the demand of adaptive geocoding engine construction driven by Big Geo-Data, when Web 2.0 techniques popularize and mobile devices that are capable of location-awareness become prevalent. The traditional geocoding service, which maintains gazetteers manually or semi-automatically by authoritative mapping agencies, cannot satisfy the needs of the latest researches. In order to solve the problems related to efficient storage and manipulation of massive Geo-Data in GIScience and related fields, our research proposes a method to build the adaptive geocoding engine in a geo-data-driven approach using Storm, a real-time and stream computing platform, thus to process multi-source network spatio-temporal data in real-time and accelerate the progression of building and maintaining gazetteers. Based on these data, an adaptive matching method of geocoding is built on the next stage. A prototype system of geocoding engine based on Storm is designed and implemented, which can process and geocode the multiple-source Geo-Data effectively. Experiments that were conducted on the POI datasets from Baidu reveals a high matching rate, which is more than 98%, and a accuracy rate of above 95%, while the average corresponding time per geocoding is about 75ms, which is practically applicable. The cases certify that real-time Storm-based streaming spatial operations not only consume an order of magnitude less time than traditional desktop stand-alone operations, but also enhance the matching rate and improve the positioning precision, which implies that the proposed solution is both feasible and practically effective. Our work offers new insights on collecting and processing POI datasets, enriching and building gazetteers, improving geocoding results in real-time with the use of Storm clusters. It makes contributions to apply real-time streaming computation methods to GIS for the state-of-the-art of Geo-Data computing, analytics and mining.

Key words: geocoding, real-time stream processing, Big Geo-Data, Storm