CPL: Enhancing Mobile Phone Functionality by Call Predicted List

Authors:
Santi Phithakkitnukoon;Ram Dantu
Affiliations:
Dept. of Comp. Sci. & Eng., University of North Texas, Denton, USA TX 76203;Dept. of Comp. Sci. & Eng., University of North Texas, Denton, USA TX 76203
Venue:
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
Year:
2008

Citing 0
Cited 4

An adaptive speed-call list algorithm and its evaluation with ESM

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Activity-aware map: identifying human daily activity pattern using mobile phone data

HBU'10 Proceedings of the First international conference on Human behavior understanding
Mining individual mobility patterns from mobile phone data

Proceedings of the 2011 international workshop on Trajectory data mining and analysis
Sensing urban mobility with taxi flow

Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we present a concept of a new advanced feature for a mobile phone that provides its user functionality for predicting future calls. The feature is envisaged as a Call Predicted List (CPL) which makes use of the user's call history to build a probabilistic model of calling behavior based on the caller's calling patterns and reciprocity. The calling behavior model is then used to generate a list of numbers/contacts that are the most likely to be callers in the next hour. The performance of the CPL is evaluated with the real-life call logs and it shows promising results in accuracy.