ACL 2010

Thuy Dung Nguyen

Outlines Our group work: keyprhase extraction system

Invited talks Towards a Psycholinguistics of Social Interaction by

Zenzi M Griffin, University of Texas at Austin Computational Advertising by Andrei Broder,

Yahoo! Research

IBM best student paper Extracting Social Networks from Literary Fiction by

David Elson, Nicholas Dames and Kathleen McKeown

SemEval Task 5: Keyphrase Extraction for Scientific Articles Our approach: utilize document logical structure (given

by ParsCit) identify which sections of the document contain the most

keyphrases shorten input text to contain only those sections: title, abstract,

introduction, related works, conclusion & 1st sentence of each paragraph of other sections

Þ increase precision but not sacrify recall.Þ final result : ranked 2nd out of 19 teams.

Other approaches: make use of document logical structure similar features: TFIDF, first occurrence, phrase length,

phrase’s occurrence in important sections, statistics of co-usage of keyphrases in large publication repository (HAL, Europarl)

Invited talk 1Study which factors influence errors in

addressing peopleby name

Shared roles Similar social relationship (boyfriend/girlfriend, family

members, dependants) Shared features

Gender, age, physical similarity Same initial sound in name (Cathy, Ken)

Invited talk 2 Computational Advertising Challenge: find “best match" between a given user

in a given context and a suitable advertisement.

Previous approach: matching based on similar words/phrases in both the webpage and the ad

Yahoo! Research: not only matches ads based on keywords but on the general topic. Classify webpages and ads into large tree of topics Map ad and webpage to a specific node on the tree Leverage the nodes for better matching

IBM best student paperExtracting Social Networks from Literary Fictions Construct social networks among characters

in 19th century British novels Provide evidence that these networks do not

fit 2 theories provided by literacy scholars There is an inverse correlation between the

amount of the dialogue and the number of characters

Novel setting (urban or rural) would have an effect on the structure of social network - more interactions occurring in rural communities than urban communities

IBM best student paper What’s the application of the research?

Using statistical method to test the validity of theories about social interaction in real world and their representation in novels

Others Best long paper

Beyond NomBank: A Study of Implicit Arguments for Nominal Predicates by Matthew Gerber and Joyce Chai

Challenge paper The Human Language Project: Building a

Universal Corpus of the World’s Languages, by Steven Abney and Steven Bird