- An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet
- Empirical Methods for Exploiting Parallel Texts I. Dan Melamed
- Naive Bayes as a Satisficing Model Ted Pedersen
- Computational Approaches to Measuring the Similarity of Short Contexts: A Review of Applications and Methods
- Adapting the Lesk Algorithm for Word Sense Disambiguation to WordNet
- How many different "John Smiths", and who are they? Anagha Kulkarni and Ted Pedersen
- SenseRelate
- Improved Unsupervised Name Discrimination with Very Wide Bigrams
- UMLS-Interface and UMLS-Similarity : Open Source Software for
- The Balancing Act: Combining Symbolic and Statistical Approaches to Language,
- Abbreviation and Acronym Disambiguation in Clinical Discourse Serguei Pakhomov, PhD1
- A Simple Approach to Building Ensembles of Naive Bayesian Classi ers for Word Sense Disambiguation
- Curriculum Vitae Ted Pedersen
- Appears in the Proceedings of the Fifteenth National Conference on Artificial Intelligence, July 1998, Madison, WI Raw Corpus Word Sense Disambiguation \Lambda
- A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation
- A Comparative Study of Supervised Learning as Applied to Acronym Expansion in Clinical Reports
- Appears in the Proceedings of the Fourteenth National Conference on Artificial Intelligence, July 1997, Providence, RI Knowledge Lean Word Sense Disambiguation \Lambda
- Appears in the Proceedings of the 5th Conference on Applied Natural Language Processing (ANLP97), April 1997, Washington, DC
- UMND1: Unsupervised Word Sense Disambiguation Using Contextual Semantic Relatedness
- Evaluating the Effectiveness of Ensembles of Decision Trees in Disambiguating Senseval Lexical Samples
- Information Content Measures of Semantic Similarity Perform Better Without Sense-Tagged Text
- Introducing an Object Oriented Design to the Ngram Statistics Package
- Comparing Supervised and Unsupervised Classification of Messages in the Enron Email Corpus
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of master's thesis by
- Unsupervised Discrimination and Labeling of Ambiguous Names
- Appears in the Proceedings of the Fifteenth National Conference on Artificial Intelligence, July 1998, Madison, WI Dependent Bigram Identification \Lambda
- A Baseline Methodology for Word Sense Disambiguation
- Appears in the Proceedings of the Fourteenth National Conference on Artificial Intelligence, July 1997, Providence, RI Naive Mixes for Word Sense Disambiguation \Lambda
- Towards Improving Synonym Options in a Text Modification Application
- Assessing System Agreement and Instance Difficulty in the Lexical Sample Tasks of SENSEVAL-2
- Using WordNet-based Context Vectors to Estimate the Semantic Relatedness of Concepts
- SenseRelate
- Extended Gloss Overlaps as a Measure of Semantic Relatedness Satanjeev Banerjee
- Guaranteed Pre{Tagging for the Brill Tagger Saif Mohammad and Ted Pedersen
- Combining Lexical and Syntactic Features for Supervised Word Sense Disambiguation
- Discovering Identities in Web Contexts with Unsupervised Clustering Ted Pedersen
- The Effect of Different Context Representations on Word Sense Discrimination in Biomedical Texts
- Determining the Syntactic Structure of Medical Terms in Clinical Notes Bridget T. McInnes
- UMND2 : SenseClusters Applied to the Sense Induction Task of SENSEVAL-4
- Determining Smoker Status using Supervised and Unsupervised Learning with Lexical Features
- Kernel Methods for Word Sense Disambiguation and Acronym Expansion Mahesh Joshi Ted Pedersen
- An End-to-end Supervised Target-Word Sense Disambiguation System Mahesh Joshi1
- 6 Unsupervised corpus-based methods for WSD Ted Pedersen
- An Unsupervised Language Independent Method of Name Discrimination Using Second
- Identifying Similar Words and Contexts in Natural Language with SenseClusters
- SenseClusters: Unsupervised Clustering and Labeling of Similar Contexts Anagha Kulkarni and Ted Pedersen
- Maximizing Semantic Relatedness to Perform Word Sense Disambiguation
- Name Discrimination by Clustering Similar Contexts
- Improving Word Sense Discrimination with Gloss Augmented Feature Vectors
- Incorporating Bigram Statistics to Spelling Correction Tools Bridget Thomson McInnesa
- SenseClusters -Finding Clusters that Represent Word Senses Amruta Purandare and Ted Pedersen
- WordNet
- The Duluth Lexical Sample Systems in SENSEVAL-3 Ted Pedersen
- Complementarity of Lexical and Simple Syntactic Features: The SyntaLex Approach to SENSEVAL-3
- Writing About Research Or, the Art of WAR
- Book Reviews Empirical Methods for Exploiting Parallel Texts
- A Plagiarism Case Study By Ted Pedersen
- LEARNING PROBABILISTIC MODELS OF WORD SENSE DISAMBIGUATION
- Appears in the Proceedings of the South-Central SAS Users Group Conference (SCSUG-96), Austin, TX, Oct 27-29, 1996 Fishing for Exactness
- Appears in the Proceedings of the 13th National Conference on Arti cial Intelligence, August 1996, Portland, OR Signi cant Lexical Relationships
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of master's thesis by
- Semantic Relatedness Applied to All Words Sense Disambiguation
- Supervised and Knowledge-based Methods for Disambiguating Terms in Biomedical Text using the
- Curriculum Vitae Ted Pedersen
- Identifying Sets of Related Words from the World Wide Web SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of master's thesis by
- University of Minnesota This is to certify that I have examined this copy of
- Unsupervised Word Sense Discrimination By Clustering Similar Contexts
- Supervised Methods for Automatic Acronym Expansion in Medical Text
- FINAL REPORT Measuring Semantic Relatedness using a Medical Taxonomy
- Building Resources for Languages with Scarce Resources By: Brian Rassier
- Identifying Word Translations in Parallel Corpora Using Measures of Association
- Advanced Search Tools for Online Resources By: Justin Chase
- Tools and Techniques for Automatic Bilingual Lexicon Construction By: Brian Rassier
- Duluth-WSI: SenseClusters Applied to the Sense Induction Task of SemEval-2
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of master's thesis by
- Extending the Log Likelihood Measure to Improve Collocation Identification SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of Master's thesis by
- Using UMLS Concept Unique Identifiers (CUIs) for Word Sense Disambiguation
- Towards a framework for developing semantic relatedness reference standards Serguei V.S. Pakhomov a,c,
- Learning High Precision Rules to Make Predictions of Morbidities in Discharge Summaries
- Discriminating Among Word Meanings By Identifying Similar Contexts Amruta Purandare and Ted Pedersen
- One Jump Ahead: Challenging Human Supremacy in Checkers,
- Appears in the Proceedings of the Pacific Asia Conference on Expert Systems, February 1112 1999, Los Angeles, CA
- Exploration of Three Cluster Stopping Rules for the task of
- Extended Gloss Overlaps as a Measure of Semantic Relatedness Satanjeev Banerjee
- Resolving Ambiguities in Biomedical Text With Unsupervised Clustering Approaches
- Discriminating Among Word Senses Using McQuitty's Similarity Analysis Amruta Purandare
- A Decision Tree of Bigrams is an Accurate Predictor of Word Sense
- Appears in the Working Notes of the AAAI Spring Symposium on Representation and Acquisition of Lexical Knowledge: Polysemy, Ambiguity, and Generativity, pages 118122, Palo Alto, CA, March 27--29, 1995
- Machine Learning with Lexical Features: The Duluth Approach to Senseval-2
- Appears in the Proceedings of the Fifteenth National Conference on Arti cial Intelligence, July 1998, Madison, WI Knowledge Lean Word{Sense Disambiguation
- UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of master's thesis by
- Appears in the Proceedings of the Fourteenth National Conference on Artificial Intelligence, July 1997, Providence, RI A New Supervised Learning Algorithm
- Appears in the Working Notes of the AAAI Spring Symposium on Search Techniques for Problem Solving Under Uncertainty and Incomplete Information, March 22--24, 1999, Palo, Alto, CA
- Semantic Similarity and Relatedness between Clinical Terms: An Experimental Study
- Ted Pedersen This paper presents a corpus{based approach to word sense disambiguation
- Measures of semantic similarity and relatedness in the biomedical domain
- Measuring Semantic Relatedness Using a Medical
- Automatic Cluster Stopping with Criterion Functions and the Gap Statistic Ted Pedersen and Anagha Kulkarni
- Unsupervised Discrimination of Person Names in Web Contexts
- The University of Minnesota Graduate School
- Using Measures of Semantic Relatedness for Word Sense Disambiguation
- The Design, Implementation and Use of the Ngram Statistics Package
- Appears in the Proceedings of the 5th Conference on Applied Natural Language Processing (ANLP-97), April 1997, Washington, DC
- Appears in the Proceedings of the Fourteenth National Conference on Arti cial Intelligence, July 1997, Providence, RI A New Supervised Learning Algorithm
- Random Walk on WordNet to Measure Lexical Semantic Relatedness
- Semantic Relatedness Study Using Second Order Co-occurrence Vectors Computed from Biomedical
- Knowledge-based Method for Determining the Meaning of Ambiguous Biomedical Terms Using Information Content Measures of Similarity
- Measuring the Similarity and Relatedness of Concepts in the Medical Domain : IHI 2012 Tutorial Overview
- Open Access Full open access to this and
- Measuring the Similarity and Relatedness of Concepts in the
