摘要
以北京公交论坛为研究对象,应用自然语言处理的方法进行海量非结构化数据的挖掘,实现公交出行需求挖掘。利用计算机技术和数学模型对原始的公交线路规划建议进行调整和优化,测算新增线路经济效益,通过筛选和排序获得北京公交线路优化方案推荐列表。
The paper uses natural language processing methods to conduct mining of vast amounts of unstructured data based on Beijing bus forums to gather citizen＇s public transport travel requirements. It also applies computer techniques and mathematical models into adjustment and optimization of original advices of public transport route planning and into economic efficiency forecast on new public traffic lines. Through filtering and sorting, recommendation list of Beijing public transport route optimization is obtained.
出处
《电脑编程技巧与维护》
2014年第8期125-127,共3页
Computer Programming Skills & Maintenance
基金
北京高等学校青年英才计划项目(YETP0847)
中央高校基本科研业务费专项资金(2012XJ031)
清华大学自主科研计划
2010年度高等学校博士学科点专项科研基金(20100002110082)资助
关键词
公交线路规划
数据挖掘
命名实体抽取
聚类
数学模型
public transportation route planning
data mining
named entity extraction
clustering
mathematic model
