一种基于多态关联挖掘的位置服务优化查询方法

Optimized Query Method of Location-based Service with Polymorphic Association Mining

高效可靠的位置服务查询方法是位置服务广泛应用的关键。传统的位置服务查询方法采用近邻查询的方法,在对近邻的分割时往往面临稳定性差的问题,无法实现高效查询。提出一种基于多态关联挖掘的位置服务优化查询方法,该方法根据查询标准,将数据分为多个状态,然后对多个状态进行关联挖掘,提取数据的深层次特征,根据深层次特征,对位置服务的查询方法进行优化查询来提高系统查询的效率和可靠性。采用查全率和查准率作为衡量标准,对200组数据进行了实际分析,结果显示,基于多态关联挖掘的位置服务查询方法使查全率和查准率分别提高9.5%和8.8%,研究成果在位置服务和信息挖掘中具有很好的应用价值。

High efficient and reliable location-based service （LBS） is key for the wide use of LBS. In traditional method, the neighbor query of location-based services query is used, and the neighborhood stability is often faced with the prob- lem of poor ability, so it is unable to achieve high efficient query. An optimized query method of location-based service with polymorphie association mining was proposed. According to the search criteria, the data is divided into more than one state, then the multiple state association mining is carried out, and the depth features of data were extracted, and ac- cording to the deep-seated characteristics of the location services available method, the efficiency and reliability of the system queries are improved. An actual analysis was carried out using a team of 200 groups of data, and the result shows that with polymorphic association mining method, the recall and precision rate are increased by 9. 50% and 8. 8%, so it has a good application value in LBS and information mining.