27 Result(s)

Article

Introduction: Special Issue on Anaphora Resolution in Machine Translation and Multilingual NLP

Ruslan Mitkov in Machine Translation (1999)

Article

Multilingual Anaphora Resolution

This paper presents amultilingual robust, knowledge-poor approach to resolvingpronouns in technical manuals. This approach is a modification of the practicalapproach (Mitkov 1998a) and operates on texts pre-pr...

Ruslan Mitkov in Machine Translation (1999)

Chapter and Conference Paper

Enhancing Preference-Based Anaphora Resolution with Genetic Algorithms

The paper argues that a promising way to improve the success rate of preference-based anaphora resolution algorithms is the use of machine learning. The paper outlines MARS - a program for automatic resolution...

Constantin OrĂsan, Richard Evans, Ruslan Mitkov in Natural Language Processing — NLP 2000 (2000)

Chapter and Conference Paper

Outstanding Issues in Anaphora Resolution

This paper argues that even though there has been considerable ad- vance in the research in anaphora resolution over the last 10 years, there are still a number of outstanding issues. The paper discusses sever...

Ruslan Mitkov in Computational Linguistics and Intelligent Text Processing (2001)

Chapter and Conference Paper

Automatic Anaphora Resolution: Limits, Impediments, and Ways Forward

The talk will discuss both the limits of and impediments to automatic anaphora resolution and will provide suggestions as to how to overcome some of these hurdles. To start with, anaphora resolution will be in...

Ruslan Mitkov in Advances in Natural Language Processing (2002)

Chapter and Conference Paper

A New, Fully Automatic Version of Mitkov’s Knowledge-Poor Pronoun Resolution Method

This paper describes a new, advanced and completely revamped version of Mitkov’s knowledge-poor approach to pronoun resolution [21]. In contrast to most anaphora resolution approaches, the new system, referred to...

Ruslan Mitkov, Richard Evans… in Computational Linguistics and Intelligent … (2002)

Article

Finding translations for low-frequency words in comparable corpora

Statistical methods to extract translational equivalents from non-parallel corpora hold the promise of ensuring the required coverage and domain customisation of lexicons as well as accelerating their compilat...

Viktor Pekar, Ruslan Mitkov, Dimitar Blagoev, Andrea Mulloni in Machine Translation (2006)

Chapter and Conference Paper

Anaphora Resolution: To What Extent Does It Help NLP Applications?

Papers discussing anaphora resolution algorithms or systems usually focus on the intrinsic evaluation of the algorithm/system and not on the issue of extrinsic evaluation. In the context of anaphora resolution, e...

Ruslan Mitkov, Richard Evans… in Anaphora: Analysis, Algorithms and Applica… (2007)

Article

Methods for extracting and classifying pairs of cognates and false friends

The identification of cognates has attracted the attention of researchers working in the area of Natural Language Processing, but the identification of false friends is still an under-researched area. This pap...

Ruslan Mitkov, Viktor Pekar, Dimitar Blagoev, Andrea Mulloni in Machine Translation (2007)

Chapter and Conference Paper

Identification of Translationese: A Machine Learning Approach

This paper presents a machine learning approach to the study of translationese. The goal is to train a computer system to distinguish between translated and non-translated text, in order to determine the chara...

Iustina Ilisei, Diana Inkpen… in Computational Linguistics and Intelligent … (2010)

Chapter and Conference Paper

Unsupervised Relation Extraction Using Dependency Trees for Automatic Generation of Multiple-Choice Questions

In this paper, we investigate an unsupervised approach to Relation Extraction to be applied in the context of automatic generation of multiple-choice questions (MCQs). MCQs are a popular large-scale assessment...

Naveed Afzal, Ruslan Mitkov, Atefeh Farzindar in Advances in Artificial Intelligence (2011)

Chapter and Conference Paper

Coreference Resolution: To What Extent Does It Help NLP Applications?

This paper describes a study of the impact of coreference resolution on NLP applications. Further to our previous study [1], in which we investigated whether anaphora resolution could be beneficial to NLP appl...

Ruslan Mitkov, Richard Evans, Constantin Orăsan… in Text, Speech and Dialogue (2012)

Chapter and Conference Paper

Ranking Machine Translation Systems via Post-editing

In this paper we investigate ways in which information from the post-editing of machine translations can be used to rank translation systems for quality. In addition to the commonly used edit distance between ...

Wilker Aziz, Ruslan Mitkov, Lucia Specia in Text, Speech, and Dialogue (2013)

Chapter and Conference Paper

Statistical Relational Learning to Recognise Textual Entailment

We propose a novel approach to recognise textual entailment (RTE) following a two-stage architecture – alignment and decision – where both stages are based on semantic representations. In the alignment stage t...

Miguel Rios, Lucia Specia, Alexander Gelbukh… in Computational Linguistics and Intelligent … (2014)

Article

Automatic generation of multiple choice questions using dependency-based semantic relations

In this paper, we present an unsupervised dependency-based approach to extract semantic relations to be applied in the context of automatic generation of multiple choice questions (MCQs). MCQs also known as mu...

Naveed Afzal, Ruslan Mitkov in Soft Computing (2014)

Chapter

Simple or Not Simple? A Readability Question

Text Simplification (TS) has taken off as an important Natural Language Processing (NLP) application which promises to offer a significant societal impact in that it can be employed to the benefit of users wit...

Sanja Štajner, Ruslan Mitkov… in Language Production, Cognition, and the Le… (2015)

Chapter and Conference Paper

A Dynamic Programming Approach to Improving Translation Memory Matching and Retrieval Using Paraphrases

Translation memory tools lack semantic knowledge like paraphrasing when they perform matching and retrieval. As a result, paraphrased segments are often not retrieved. One of the primary reasons for this is th...

Rohit Gupta, Constantin Orăsan, Qun Liu, Ruslan Mitkov in Text, Speech, and Dialogue (2016)