基于大数据的网约车服务推荐研究

基于大数据的网约车服务推荐研究(任务书,开题报告,论文14000字)
摘要
随着网约车行业的高速发展，其行业竞争也日益激烈，各个平台越发注重增加用户数量以提升市场占有率。但是很长一段时间以来网约车的服务质量参差不齐，缺乏个性化的问题一直饱受诟病。在互联网和大数据技术迅速普及的今天，网约车平台要想占领市场地位，就必须提高自身的信息化建设，为消费者提供智能化、个性化、专业化的出行服务。
针对目前我国网约车市场存在的个性化不足的问题，本文在充分考虑了包括车辆信息和司机服务等用户偏好以及路线一致性、交通情况和供需关系等情境条件，提出了基于用户偏好的静态服务推荐算法和基于用户情境的动态服务推荐算法。这两种算法可以在用户出行前和出行过程中为用户提供精准的个性化服务推荐。通过对用户偏好、用户情境建模，分别实现两种推荐算法，为今后网约车平台在个性化服务推荐系统方面提供理论依据。
关键词：大数据；网约车；服务推荐；用户偏好；用户情境
 
Abstract
With the high-speed development of network about the car industry, the industry competition is increasingly fierce, the platform even more pay attention to increase the number of users in order to enhance the market share.But for a long time about car service quality is uneven, the lack of personalized problem has been to ridicule.In the Internet and the rapid spread of big data technology today, network platform about car want to occupy the market position, it is necessary to improve their information construction, provide consumers with intelligent, personalized, professional travel service.
View of the network in China car market is about the problem of insufficient of personalized, after fully considering the information including the vehicle and the driver services user preferences and route consistency conditions, traffic conditions and relationship between supply and demand situation, puts forward the static services recommendation algorithm based on user preferences and dynamic service recommendation algorithm based on user Settings.These two algorithms can be in the process of user before a trip and travel to provide users with accurate personalized recommendation service.Based on user preferences, user context modeling, respectively, two kinds of recommendation algorithm for the network about car platform provides the theoretical basis in the personalized services recommendation system.
Key Words：Big data;Net about car;Servicesrecommended;Userpreferences;The user Settings
 
目录
第1章绪论    6
1.1 研究背景    6
1.2 研究目的与意义    6
1.3 国内外网约车研究现状    7
1.3.1 国内现状    7
1.3.2 国外现状    8
第2章网约车服务推荐发展现状    9
2.1 现有模式    9
2.1.1信用评级指标    9
2.1.2地理位置指标    9
2.1.3情境感知指标    9
2.2 存在的问题——参照指标过于单一    10
第3章网约车服务推荐建模    11
3.1 偏好建模    11
3.1.1偏好模型定义    11
3.1.2偏好模型因素    11
3.1.2偏好模型构建    11
3.2 情境建模    12
3.2.1情境模型定义    12
3.2.1情境模型因素    13
3.2.2情境模型建模    14
第4章网约车服务个性化推荐算法    16
4.1 基于用户偏好的静态推荐    16
4.2 基于用户情境的动态推荐    17
4.2.1情境化用户偏好建模    17
4.2.2基于用户情境的个性化推荐    17
第5章结语    20