TitleExtending word highlighting in multiparticipant chat
Publication TypeConference Paper
Year of Publication2013
AuthorsUthus, DC, Aha, DW
Conference NameFlorida Artificial Intelligence Research Society Conference
PublisherAAAI Press
Conference LocationSt. Pete Beach, FL
Keywordschat analysis, machine learning, word highlighting
Abstract

We describe initial work on extensions to word highlighting
for multiparticipant chat to aid users in finding messages of
interest, especially during times of high traffic in chat rooms.
We have annotated a corpus of chat messages from a technical
chat domain (Ubuntu’s technical support), indicating whether
they are related to Ubuntu’s new desktop environment Unity.
We also created an unsupervised learning algorithm, in which
relations are represented with a graph, and applied this to find
words related to Unity so they can be highlighted in new, unseen
chat messages. On the task of finding relevant messages,
our approach outperformed two baseline approaches that are
similar to current state-of-the-art word highlighting methods
in chat clients.

Refereed DesignationRefereed
Full Text
pdf: 
http://www.nrl.navy.mil/itd/aic/sites/www.nrl.navy.mil.itd.aic/files/pdfs/%28Uthus%20%26%20Aha%2C%20FLAIRS-13%29%20Extending%20Word%20Highlighting%20in%20Multiparticipant%20Chat.pdf
NRL Publication Release Number: 
12-1231-4614
pub_tags: 
machine learning
chat analysis
word highlighting
key_pub_tags: