LogMin: A Model For Call Log Mining In Mobile Devices

TL;DR

LogMin is a new model for mining call logs on mobile devices that helps users understand call patterns and trends, validated through an Android prototype showing high relevancy accuracy.

Contribution

The paper introduces LogMin, a novel call log mining model that analyzes six parameters to reveal usage patterns, validated with an Android prototype.

Findings

Achieved 96.52% user relevancy metric.

Validated model effectiveness through experiments on Android.

Demonstrated pattern discovery in call logs.

Abstract

In today's instant communication era, mobile phones play an important role in the efficient communication with respect to both individual and official communication strata. With the drastic explosion in the quantity of calls received and made, there is a need for analyses of patterns in these call logs to assist the user of the mobile device in the optimal utilization. This paper proposes a model termed "LogMin" (Log Mining of Calls in Mobile devices) which is aimed towards mining of call log in mobile phones to discover patterns and keep the user informed about the trends in the log. The logging of calls would facilitate the user to get an insight into patterns based on the six different parameters identified by the proposed LogMin model. The proposed model is validated with a prototype implementation in the Android platform and various experiments were conducted on it. The results of the experiments in the LogMin Android implementation validate the efficiency of the proposed model with respect to user's relevancy metric which is computed as 96.52%.