| 基于铁路出行数据的旅客常住地智能识别算法研究 |
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| 引用本文： | 郭根材.基于铁路出行数据的旅客常住地智能识别算法研究[J].铁路计算机应用,2018,27(11):40-42. |
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| 作者姓名： | 郭根材 |
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| 作者单位： | 中国铁道科学研究院集团有限公司 电子计算技术研究所,北京 100081 |
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| 基金项目： | 国家重点研发计划项目（2018YFB1201404）；中国铁路总公司科研计划课题（2016X005-D） |
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| 摘 要： | 常住地是判断旅客消费能力与收入水平的重要因素，利于根据旅客常住地进行个性化产品推荐。针对铁路客票发售与预订系统的海量出行数据，依据逻辑判断与概率计算设计了铁路旅客常住地智能识别算法；最后利用Scala语言在铁路客运大数据平台上实现算法，并针对最近两年铁路旅客出行数据进行案例验证，结论表明:该算法有效，旅客常住地信息的识别率为67.7%。
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| 关 键 词： | 铁路出行数据 大数据技术 常住地 智能识别算法 |
| 收稿时间： | 2018-05-09 |
Intelligent recognition algorithm of passengers permanent residence based on railway travel data |
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| Affiliation: | Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited,Beijing 100081, China |
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| Abstract: | Permanent residence is an important factor of passenger’s consumption ability and income level, which is conducive to accomplish personalized recommendation. According to the travel data of Railway Ticketing and Reservation System, this article designed an intelligent recognition algorithm to infer the railway passenger’s permanent residence through logical judgment and probability statistics, used Scala language to implement algorithm on large data platform of railway passenger transport. Based on the case study of railway passenger travel data in recent two years, the conclusion shows that the algorithm is effective and the recognition rate of passenger permanent residence is 67.7%. |
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