Location Prediction Model Based on K-Means Algorithm and Time Matching
[1]Hu Yan,Zhu Xiaoying,Ma Gang.Location Prediction Model Based on K-Means Algorithm and Time Matching[J].Journal of Zhengzhou University (Engineering Science),2017,38(02):17-20.[doi:10.13705/j.issn.1671-6833.2017.02.005]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
38
Number of periods:
2017 02
Page number:
17-20
Column:
Public date:
2017-04-28
- Title:
- Location Prediction Model Based on K-Means Algorithm and Time Matching
- Keywords:
- location prediction; K-Means algorithm; time matching; cluster
- CLC:
- -
- Abstract:
- Location prediction was critical to mobile service because various kinds of applications were tightly combined with user’s location.However,location prediction was a challenging work because location capturing was always not continuous and user’ s behavior were uncertain and irregular.To improve the location prediction accuracy rate,this paper proposed a location prediction model based on K-Means algorithm and time matching.For the mobile service always region oriented,we first clusted history location using K-Means algorithm to define several regions.Then we divided every day time into several segments and calculated the maximum probability location in every time segment.A trajectory of a user in one day was formed with trajectory model and trajectory updating model which proposed in this paper.We could predict user’ location with time matching method.At last,we did experiments with real location data in campus which captured by APs.The prediction out come with K-Means was compared to the outcome without model based on K-Means algorithm.The experiment result shows that accuracy rate of our model was higher than the prediction without new model.So,more location services could be provided to users with this new model.
- References:
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