面向位置偏好查询的移动P2P数据库构建及算法研究

Preference query processing has received a considerable amount of attention due to its potential applications in many scenarios, including in those involving traditional, distributed databases, and even the categorical databases and so on.As an important data mining and data analysis technique, preference query is of great significance for application areas such as urban navigation, data mining visualization, e-commerce, multi-criteria decision making and preference-based search, trip planning, defense intelligence systems and geographic information systems. On the other hand, with the recent advance of wireless communication and mobile technologies,the mobile P2P computing is an emerging area that is attracting increasing attention from multiple research communities and industry sectors.The aim of this project will significantly improve the performance of mobile P2P applications by adding a much desired level of sophistication to current P2P data management technology.Towards efficient location-aware preference search in mobile P2P applications, we propose PreferPeer, a mobile P2P database architecture, as a practical and powerful solution. The expected outcome of this project is to provide a complete database solution for mobile P2P applications. Our research is leading the international effort of extending database technologies to support data management and search for very large scale highly mobile data.Moreover,we propose PDA,an interactive personal decision assistant system based on mobile P2P database,for people to get the desired optimal decision easily.

偏好查询处理在集中式、分布式、及分类属性数据库上具有良好的应用前景，已成为当前数据库界研究的热点之一。它作为一种广泛应用于多标准决策系统、数据挖掘可视化、用户约束决策、城市导航系统、智能防御系统、以及地理信息系统等领域的新型数据挖掘技术，该问题的研究迄今为止都非常活跃。另一方面，随着无线通信和移动定位等技术的快速发展，移动通信和互联网的日益普及，移动P2P计算也成为越来越多的研究团队和工业界所关注的新兴领域。本研究通过对当前P2P数据管理技术的改进，旨在提高移动P2P应用的性能。针对移动P2P应用上的高效定位感知偏好搜索，提出了移动P2P数据库框架PreferPeer。项目的预期研究结果是为移动P2P应用提供一个完善的数据库解决方案，致力于扩展数据库技术以支持数据管理和大规模移动数据的偏好查询处理，并设计一个交互式个人决策支持系统，该系统的目的是方便根据用户偏好获取所需的最优决策。

偏好查询处理在集中式数据库、分布式数据库、数据流及分类属性数据集上的良好应用前景，使其成为当前数据库界研究的重点和热点之一，受到了学术界和工业界的广泛关注。通常我们熟知的Skyline、Top-k、NN/RNN等都属于偏好查询处理问题。例如，Skyline查询返回一组有意义的对象，这些对象在各维上都不被其他对象所控制，从而支持用户在复杂的情况下进行决策，它作为一种广泛应用于多标准决策系统、数据挖掘可视化、电子商务、用户约束决策、城市导航系统、智能防御系统、以及地理信息系统等领域的新型数据挖掘技术和典型偏好查询处理问题的代表，该问题的研究迄今为止都非常活跃。.本项目将在对现有技术之不足进行改进的基础上，进一步解决一些新型重要的实际应用带来的对偏好查询处理的挑战。基于对偏好查询处理问题的研究，本项目拟设计一个交互式的个人决策支持系统——PDA (Personal Decision Assistant)，该系统的目的是方便根据用户偏好获取所需的最优决策。