"基于Android的在线拍卖数据分析与预测系统设计与实现"

The development of Internet technology and the widespread use of the Internet have brought about significant changes in the traditional auction industry. In response to this trend, this paper presents the design and implementation of an online auction data analysis and auction prediction system. The system is developed based on the Android studio environment and SQLite database, providing a stable platform for auction transactions between buyers and sellers. Key features of the system include login and registration functionalities, bidding, item management, viewing won items, browsing unsold items, and managing auction categories. The use of the Android platform ensures that users can easily access the system from their mobile devices, making it convenient for both buyers and sellers to participate in online auctions. Through data analysis, the system is able to provide valuable insights into auction trends and patterns, enabling users to make informed decisions when placing bids. Additionally, the auction prediction feature uses machine learning algorithms to forecast the final selling price of auctioned items, helping users strategize and optimize their bidding strategies. Overall, the online auction data analysis and auction prediction system presented in this paper offers a comprehensive and user-friendly platform for conducting online auctions efficiently and effectively. By leveraging the power of technology and data analysis, this system aims to enhance the overall auction experience for both buyers and sellers in the online marketplace.