MailCat: an intelligent assistant for organizing e-mail
Proceedings of the third annual conference on Autonomous Agents
Machine Learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
A Memory-Based Approach to Anti-Spam Filtering for Mailing Lists
Information Retrieval
Combining email models for false positive reduction
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Context-aware telephony: privacy preferences and sharing patterns
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Socio-technical defense against voice spamming
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Detecting spam in VoIP networks
SRUTI'05 Proceedings of the Steps to Reducing Unwanted Traffic on the Internet on Steps to Reducing Unwanted Traffic on the Internet Workshop
Finding similar files in a large file system
WTEC'94 Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference
Improving cell phone awareness by using calendar information
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
A Survey of Voice over IP Security Research
ICISS '09 Proceedings of the 5th International Conference on Information Systems Security
Mobile social closeness and communication patterns
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
A testbed for large mobile social computing experiments
International Journal of Sensor Networks
Towards ubiquitous computing with call prediction
ACM SIGMOBILE Mobile Computing and Communications Review
Behavior-based adaptive call predictor
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
| Hi-index | 0.00 |
In our everyday life, we communicate with many people such as family, friends, neighbors, and colleagues. We communicate with them using different communication media such as email, telephone calls, and face-to-face interactions. While email is not real-time and face-to-face communications require geographic proximity, voice and video communications are preferred over other modes of communication. However, real-time voice/video calls may create nuisance to the receiver. In this article, we describe a mathematical model for computing nuisance level of incoming voice/video calls. We computed the closeness and nuisance level using the calling patterns between the caller and the callee. To validate the nuisance model, we collected cell phone call records of real-life people at our university and computed the nuisance value for all voice calls. We validated the nuisance levels using the feedback from those real-life people. Such a nuisance model is useful for predicting unwanted voice and video sessions in an IP communication network.