Predicting the location and time of mobile phone users by using sequential pattern mining techniques

Download
2014
Özer, Mert
Predicting the location of people from their mobile phone logs has become an active research area. Due to two main reasons this problem is very challenging: the log data is very large and there is a variety of granularity levels both for specifying the spatial and the temporal attributes, especially with low granularity level it becomes much more complicated to define common user behaviour patterns. For the location prediction problem domain, we focused on 3 sub-problems and proposed 3 different methods for these problems. The idea in all of the three methods follows these two steps; cluster the spatial data into the regions and group temporal data into the time intervals to get higher granularity level, and apply sequential pattern mining techniques to extract frequent movement patterns to predict accordingly. We have validated our results with real data obtained from one of the largest mobile phone operators in Turkey. Our results are very encouraging, and we have obtained very high accuracy results in predicting the location of mobile phone users.

Suggestions

Predicting the Next Location Change and Time of Change for Mobile Phone Users
Ozer, Mert; Keles, Ilkcan; Toroslu, İsmail Hakkı; Karagöz, Pınar; Ergut, Salih (2014-11-04)
Predicting the next location of people from their mobile phone logs has become an active research area. Due to two main reasons this problem is very challenging: the log data is very large and there are variety of granularity levels for specifying the spatial and the temporal attributes. In this work, we focus on predicting the next location change of the user and when this change occurs. Our method has two steps, namely clustering the spatial data into larger regions and grouping temporal data into time in...
Methods for location prediction of mobile phone users
Keleş, İlkcan; Toroslu, İsmail Hakkı; Department of Computer Engineering (2014)
Due to the increasing use of mobile phones and their increasing capabilities, huge amount of usage and location data can be collected. Location prediction is an important task for mobile phone operators and smart city administrations to provide better services and recommendations. In this work, we have investigated several approaches for location prediction problem including clustering, classification and sequential pattern mining. We propose a sequence mining based approach for location prediction of mobil...
Automated Moving Object Classification in Wireless Multimedia Sensor Networks
Civelek, Muhsin; Yazıcı, Adnan (2017-02-15)
The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires co...
Predicting the Location and Time of Mobile Phone Users by Using Sequential Pattern Mining Techniques
Ozer, Mert; Keles, Ilkcan; Toroslu, Hakki; Karagöz, Pınar; Davulcu, Hasan (2016-06-01)
In recent years, using cell phone log data to model human mobility patterns became an active research area. This problem is a challenging data mining problem due to huge size and non-uniformity of the log data, which introduces several granularity levels for the specification of temporal and spatial dimensions. This paper focuses on the prediction of the location of the next activity of the mobile phone users. There are several versions of this problem. In this work, we have concentrated on the following th...
Modelling mobile telecommunications services for forecasting purposes : a cross - country analysis
Eser, Eren; Eren, Pekin Erhan; Department of Information Systems (2012)
Mobile telecommunications industry has experienced high growth rates for the recent 30 years. Accordingly, forecasting the future of mobile telecommunications services is important not only for mobile operators but also for all stakeholders in this industry ranging from handset manufacturers to vendors. In this thesis, the diffusion of mobile telecommunications services in 20 countries from different regions around the world is examined for the period of 1981 to 2010 with special emphasis on Turkey, in orde...
Citation Formats
M. Özer, “Predicting the location and time of mobile phone users by using sequential pattern mining techniques,” M.S. - Master of Science, Middle East Technical University, 2014.