Design and Implementation of Regional Food Distribution Platform Based on Big Data

Abstract

In recent years, the rapid development of big data has made people's daily life very convenient, and at the same time, tasting all kinds of food has become an important activity for people to travel. Due to the vast territory of China, there are many types of cuisines with great differences, it is very important for travelers to understand the special regional cuisines in the area. This project aggregates regional food data based on big data, and provides tourists with efficient, stable and professional data retrieval and analysis services through a visual data interface, and provides intuitive, accurate, and real-time data support for the decision-making of finding characteristic regional food. This thesis first conducted a relevant understanding of big data and the overall situation of regional cuisine, analyzed the distribution of food in the sub-provincial city of Xi'an, explored the research methods and implementation methods of related projects at home and abroad, based on this, summarized the research of this project the goal. At the same time, the focus of this project is to analyze the price, score and popularity of regional food data analysis in my country, and to summarize, proofread and organize the data obtained before into standard and standardized data. Through the classification of basic information, the visual analysis and display of data is realized, and the key data urgently needed by decision makers are extracted from it. To analyze the needs of decision makers, establish corresponding strategies and measures to improve the quality of data services. The establishment of this system provides a useful supplement and improvement to the existing industry data analysis system. The system is mainly divided into six modules, which are data collection, data review, data summary, and visual data display modules. Among them, data collection includes crawling relevant data from the Internet and retrieving key data. The data audit function includes classifying the crawled data and reviewing its effectiveness. Data aggregation includes summarizing the filtered data in an excel table and passing Excel generates a visual chart that you want to know, and at the same time generates a word cloud by associating certain two related items in the data in the excel table. The visual data display module can more clearly show the results of data analysis to users, so that users can make better decisions. The visualization data uses AmChart Flash charts. The implementation of this system adopts Django Python Web framework, the development language chooses Python, the development tool adopted is PyCharm, and the database tool adopts MySQL.