ASAP- An Advanced System for Assessing Chat Participants

Authors:
Mihai Dascalu;Erol-Valeriu Chioasca;Stefan Trausan-Matu
Affiliations:
"Politehnica" University of Bucharest, Bucharest, Romania 060042;"Politehnica" University of Bucharest, Bucharest, Romania 060042;"Politehnica" University of Bucharest, Bucharest, Romania 060042 and Romanian Academy Research Institute for Artificial Intelligence, Bucharest, Romania
Venue:
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Year:
2008

Citing 4
Cited 3

Foundations of statistical natural language processing

Foundations of statistical natural language processing
Introduction to Algorithms

Introduction to Algorithms
Group Cognition: Computer Support for Building Collaborative Knowledge (Acting with Technology)

Group Cognition: Computer Support for Building Collaborative Knowledge (Acting with Technology)
Explicit referencing in learning chats: needs and acceptance

EC-TEL'06 Proceedings of the First European conference on Technology Enhanced Learning: innovative Approaches for Learning and Knowledge Sharing

Using the Social Web to Supplement Classical Learning

ICWL '009 Proceedings of the 8th International Conference on Advances in Web Based Learning
A deep insight in chat analysis: collaboration, evolution and evaluation, summarization and search

AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
A polyphonic model and system for inter-animation analysis in chat conversations with multiple participants

CICLing'10 Proceedings of the 11th international conference on Computational Linguistics and Intelligent Text Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

The paper presents a method and an implemented system for the assessment of the participants' competences in a collaborative environment based on an instant messenger conversation (chat). For each utterance in the chat, a score is computed that takes into account several features, specific to text mining (like the presence and the density of keywords, via synonymy), natural language pragmatics and to social networks. The total rating of the competence of a participant is computed considering the scores of utterances and inter-utterance factors. Within the frame of the developed system, special attention was given to multiple ways of visualizing the analysis' results. An annotation editor was also implemented and used in order to construct a "golden standard", which was further employed for the evaluation of the developed assessment tools.