Socio-technical defense against voice spamming
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Prediction of 9-1-1 call volumes for emergency event detection
dg.o '07 Proceedings of the 8th annual international conference on Digital government research: bridging disciplines & domains
Nuisance level of a voice call
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Predicting Calls --- New Service for an Intelligent Phone
MMNS '07 Proceedings of the 10th IFIP/IEEE International Conference on Management of Multimedia and Mobile Networks and Services: Real-Time Mobile Multimedia Services
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With the long-awaited era of the pervasive computing approaches, the handheld devices such as personal mobile phones begin to evolve into ubiquitous computing devices. At this early stage of the evolution, we propose a model of a call predictor based on the na脗篓?ve Bayesian classifier. As an incoming call predictor, our model makes use of the userâ聙聶s call history to generate a list of numbers/contacts that are the most likely to be the callers within the next hour. On the other hand, when the user wants to make an outgoing call (e.g., user flips open the phone or unlocks the phone, etc.), the outgoing call predictor generates a list of number/contacts to be called. Our model has been evaluated with the real-life call logs and it shows a promising result in accuracy.