A Dynamic Traffic Information Data Model Research Based On A Chinese Geographical Segmentation Algorithm

The traffic jams are big problems in the process of city development, so the country is vigorously developing the smart city, constructing the intelligent transportation system, in order to speeding up the optimized construction of urban public transportation, improving the capacity of public transportation information services. However, with the rapid development of traffic information, types of traffic data are more and more various, and the amount of data is increasing day by day. At the same time, the analysis and processing of dynamic traffic comprehensive data are also facing serious challenges.Facing the diversity and complexity of traffic data, only more efficient and stable data organization and management methods can effectively organize and manage different types of traffic data. At the same time, we need to explore and research on the data organization and management model, thinking about the resolution of real traffic data. We should continue to explore the spatio-temporal data model to improve the efficiency of data storage and management, paying attention to the massive data real-time processing and depth of the excavation.so the public can get rapid, accurate and efficient traffic information service to solve the daily slow bus, hard parking, walking detour. Basing on the complicated dynamic traffic information, many issues are discussed about passive traffic information service and active transport information search, and a dynamic integrated traffic information data model is raised basing on exploring Chinese geographic word segmentation method and application study has been conducted. The main works are as follows:(1) the method of Chinese geographical word segmentation is studied, and it is applied in the field of traffic geographic information. To improve the response speed of the public in the active traffic information search service, first of all, the means of traffic thematic information segmentation fast are raised; secondly, the RMM algorithm is improved, which optimizes a traffic thematic word. The algorithm can avoid the ambiguity of the professional word segmentation, and combine with the structure optimization of the traffic information dictionary, significantly improving the accuracy of the segmentation based on traffic information retrieval statement.(2) To meet the needs of the algorithm, referencing the semantic representation of the hierarchy characteristic of ontology, the storage structure of traffic information dictionary is designed. Then based on the related dynamic traffic thematic data the traffic thematic information database is established;(3) The establishment of dynamic traffic information data model based on ontology. According to the ontology modeling theory, combining with the research results of geographic ontology, the ontology model of traffic information for multi subject dynamic traffic information is built.(4) Verification of the application of the model. Taking TOCC system in Xicheng District as an example, according to the model structure of ontology, all kinds of dynamic information are classified and related. Then, the word segmentation algorithm is used to extract the traffic keywords from the user's search statement. Finally, it provides an integrated search and multi direction display for multi type dynamic traffic information.The results show that the model has a certain practical significance for the analysis and retrieval of multi-source dynamic traffic data, providing important technical reference for dynamic traffic information processing. Finally, the further research and application of dynamic comprehensive traffic information based on ontology knowledge are explored and prospected.