The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Unsupervised document classification using sequential information maximization
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Performance criteria for graph clustering and Markov cluster experiments
Performance criteria for graph clustering and Markov cluster experiments
The Journal of Machine Learning Research
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Discovering corpus-specific word senses
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
A graph model for unsupervised lexical acquisition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Automatically discovering word senses
NAACL-Demonstrations '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Demonstrations - Volume 4
Graph-based ranking algorithms for sentence extraction, applied to text summarization
ACLdemo '04 Proceedings of the ACL 2004 on Interactive poster and demonstration sessions
Characterising measures of lexical distributional similarity
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Automatic cluster stopping with criterion functions and the gap statistic
NAACL-Demonstrations '06 Proceedings of the 2006 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume: demonstrations
Word Sense Induction Using Graphs of Collocations
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Two graph-based algorithms for state-of-the-art WSD
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Semeval-2007 task 02: evaluating word sense induction and discrimination systems
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UMND2: SenseClusters applied to the sense induction task of Senseval-4
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
Random walks for text semantic similarity
TextGraphs-4 Proceedings of the 2009 Workshop on Graph-based Methods for Natural Language Processing
Structural inference of hierarchies in networks
ICML'06 Proceedings of the 2006 conference on Statistical network analysis
Taxonomy learning using word sense induction
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
SemEval-2010 task 14: Word sense induction & disambiguation
SemEval '10 Proceedings of the 5th International Workshop on Semantic Evaluation
SENSEVAL '01 The Proceedings of the Second International Workshop on Evaluating Word Sense Disambiguation Systems
Nonparametric Bayesian word sense induction
TextGraphs-6 Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing
Word sense induction by community detection
TextGraphs-6 Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing
Unsupervised semantic role induction with graph partitioning
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Taxonomy induction using hierarchical random graphs
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Evaluating unsupervised ensembles when applied to word sense induction
ACL '12 Proceedings of ACL 2012 Student Research Workshop
MaxMax: a graph-based soft clustering algorithm applied to word sense induction
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Evaluating Word Sense Induction and Disambiguation Methods
Language Resources and Evaluation
| Hi-index | 0.00 |
Graph-based methods have gained attention in many areas of Natural Language Processing (NLP) including Word Sense Disambiguation (WSD), text summarization, keyword extraction and others. Most of the work in these areas formulate their problem in a graph-based setting and apply unsupervised graph clustering to obtain a set of clusters. Recent studies suggest that graphs often exhibit a hierarchical structure that goes beyond simple flat clustering. This paper presents an unsupervised method for inferring the hierarchical grouping of the senses of a polysemous word. The inferred hierarchical structures are applied to the problem of word sense disambiguation, where we show that our method performs significantly better than traditional graph-based methods and agglomerative clustering yielding improvements over state-of-the-art WSD systems based on sense induction.