Papers for Relevance Assessment by Advaith Siddharthan

Research Question: To use language modellling to predict the most plausible realization of the information, using the aligned strings

Reformulation: To use language modeling to predict the most plausible realization of information that is common across documents, using the aligned strings

Paper ID
(Link to PDF)

Title

Author(s)

P05-2026

A Domain-Specific Statistical Surface Realizer

Jeffrey Russell

W05-1510

Probabilistic Models for Disambiguation of an HPSG-Based Chart Generator

Hiroko Nakanishi; Yusuke Miyao; Jun'ichi Tsujii

C02-1170

A Pattern-based Analyzer for French in the Context of Spoken Language Translation: First Prototype and Evaluation

Herve Blanchon

W98-1425

A FLEXIBLE SHALLOW APPROACH TO TEXT GENERATION

Stephan Busemann; Helmut Horacek

W02-1022

Bootstrapping Lexical Choice via Multiple-Sequence Alignment

Regina Barzilay; Lillian Lee

W98-1236

Language Model and Sentence Structure Manipulations for Natural Language Application Systems

Zenshiro Kawasaki; Keiji Takida; Masato Tajima

W01-0813

Applying Natural Language Generation to Indicative Summarization

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

W00-1301

Pattern-Based Disambiguation for Natural Language Processing

Eric Brill

267_pdf_2-col

Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models

Indrajit Bhattacharya, Lise Getoor and Yoshua Bengio

W96-0411

Best-First Surface Realization

Stephan Busemann

W00-1009

A Common Theory of Information Fusion from Multiple Text Sources Step One: Cross-Document Structure

Dragomir Radev

A00-2026

Trainable Methods for Surface Natural Language Generation

Adwait Ratnaparkhi

15

PolyphraZ: a Tool for the Management of Parallel Corpora

Najeh Hajlaoui and Christian Boitet

238_pdf_2-col

Statistical Machine Translation with Word- and Sentence-Aligned Parallel Corpora

Chris Callison-Burch, David Talbot and Miles Osborne

W03-0315

Efficient Optimization for Bilingual Sentence Alignment Based on Linear Regression

Bing Zhao; Klaus Zechner; Stephen Vogel; Alex Waibel