Papers for Relevance Assessment by Liang Zhou

Research Question: Not all topics from the discussions are summarized by humans, why is that?

Paper ID
(Link to PDF)

Title

Author(s)

P03-1013

Probabilistic Parsing for German Using Sister-Head Dependencies

Amit Dubey; Frank Keller

W03-0510

The Potential and Limitations of Automatic Sentence Extraction for Summarization

Chin-Yew Lin; Eduard Hovy

W97-0707

Automatic Text Summarization by paragraph Extraction

Mandar Mitrat; Amit Singhal; Chris Buckleytt

W98-0202

Intelligent Network News Reader with Visual User Interface

Hitoshi ISAHARA; Kiyotaka UCHIMOTO; Hiromi OZAKU

167_Paper

Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization

Regina Barzilay and Lillian Lee

W03-0507

Text Summarization Challenge 2 - Text summarization evaluation at NTCIR Workshop 3

Manabu Okumura; Takahiro Fukusima; Hidetsugu Nanba

W05-0907

Evaluating DUC 2004 Tasks with the QARLA Framework

Enrique Amigo; Julio Gonzalo; Anselmo Penas; Felisa Verdejo

J02-4005

Generating Indicative-Informative Summaries with SumUM

Horacio Saggion; Guy Lapalme

W01-0813

Applying Natural Language Generation to Indicative Summarization

Kan, Min-Yeh; McKeown, Kathleen R.; Klavans, Judith L.

W03-1203

Combining Optimal Clustering and Hidden Markov Models for Extractive Summarization

Pascale Fung; Grace Ngai; Chi-Shun Cheung

H05-1001

Improving LSA-based Summarization with Anaphora Resolution

Josef Steinberger; Mijail Kabadjov; Massimo Poesio; Olivia Sanchez-Graillet

W05-0902

On the Subjectivity of Human Authored Summaries

BalaKrishna Kolluru; Yoshihiko Gotoh

J02-4006

Using Hidden Markov Modeling to Decompose Human-Written Summaries

Hongyan Jing

C92-3167

Recognizing Topics through the Use of Interaction Structures

TAKESHITA, Atsushi

J02-4001

Introduction to the Special Issue on Summarization

Dragomir R. Radev; Eduard Hovy; Kathleen McKeown