Data Set Used
Text is not unadulterated fact. A text can make you laugh or cry but can it also make you short sell your stocks in company A and buy up options in company B? Research in the domain of finance strongly suggests that it can. Studies have shown that both the informational and affective aspects of news text affect the markets in profound ways, im-pacting on… (More)
Increasingly powerful fault management systems are required to ensure robustness and quality of service in today's networks. In this context, event correlation is of prime importance to extract meaningful information from the wealth of alarm data generated by the network. Existing sequential data mining techniques address the task of identifying possible… (More)
— The ongoing work presented in this paper is aimed at bringing self-configuration capabilities into next generation radio access networks. We present the main concepts and architecture of our prototype. We also introduce briefly a novel strategy for foreseeing the outcome of enforcing policies integrating behaviour discovery techniques and finite state… (More)
The field of automated sentiment analysis has emerged in recent years as an exciting challenge to the computational linguistics community. Research in the field investigates how emotion, bias, mood or affect is expressed in language and how this can be recognised and represented automatically. To date, the most successful applications have been in the… (More)
— Policy-based network management (PBNM) is a promising but not yet delivering discipline aimed at automating network management decisions based on expert knowledge and strategic business objectives. One of the issues which is almost not being addressed in PBNM is the stability of the managed system as the result of the dynamic interaction between the "… (More)
We present a means of comparing texts to highlight their informational differences. The system builds a Directed Acyclic Graph representation of the combined WordNet hypernym hierarchies of the nouns. Comparison of these yields a graph which distinguishes minor lexical & major content differences.