[PDF] Top 20 An Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation
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An Empirical Evaluation of Knowledge Sources and Learning Algorithms for Word Sense Disambiguation
... each learning algorithm, broken down ac- cording to nouns, verbs, adjectives, indeterminates (for SENSEVAL-1), and all ...four knowledge sources achieves accuracy higher than the best offi- cial ... See full document
8
Learning Expressive Models for Word Sense Disambiguation
... supervised learning (see Mihalcea et ...limited knowledge representation and modeling techniques: traditional machine learning algorithms and attribute-value vectors to represent disambigu- ... See full document
8
An Empirical Study on Class Based Word Sense Disambiguation
... on learning class-based classifiers from other available sense–groupings such as WordNet Domains (Magnini and Cavagli`a, 2000), SUMO labels (Niles and Pease, 2001), EuroWordNet Base Concepts (Vossen et ... See full document
9
Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison
... systems, knowledge- based WSD techniques do not require any sense- annotated ...manually-curated knowledge resources for ...get word and its definitions as given by the sense ...target ... See full document
12
Word Sense Disambiguation Using OntoNotes: An Empirical Study
... active learning. Hence, we perform active learning experiments on all the word types that have sense-tagged examples from OntoNotes sections 02-21, and show the evaluation results on ... See full document
9
Embeddings for Word Sense Disambiguation: An Evaluation Study
... as word senses or concepts, given that conventional embeddings conflate different meanings of a word into a sin- gle ...of word senses, instead of words (Reisinger and Mooney, 2010; Huang et ... See full document
11
An Empirical Study of the Behavior of Active Learning for Word Sense Disambiguation
... best knowledge, there have been very few attempts to apply active learning to WSD in the literature (Fujii and Inui, 1999; Chklovski and Mihalcea, 2002; Dang, ...active learning of verb senses in a ... See full document
8
Enriching Wordnet for Word Sense Disambiguation
... linguistics, word-sense disambiguation (WSD) is an open problem of natural language processing, which governs the process of identifying which sense of a word ...the word has ... See full document
6
Random Walks for Knowledge Based Word Sense Disambiguation
... walk algorithms to the Spanish WordNet (Atserias, Rigau, and Villarejo 2004), using the SemEval-2007 Task 09 data set as evaluation gold standard (M`arquez et ...our algorithms approaching MFS ... See full document
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A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
... This paper describes a set of comparative exper- iments, including cross-corpus evaluation, be- tween five alternative algorithms for supervised Word Sense Disambiguation WSD, namely Nai[r] ... See full document
6
Neural Sequence Learning Models for Word Sense Disambiguation
... Word Sense Disambiguation models ex- ist in many ...flexible knowledge-based solutions, which do not require training by a word expert for every disambiguation ...sequence ... See full document
12
The interaction of knowledge sources in word sense disambiguation
... each knowledge source separately, we imple- mented a set of simple disambiguation algorithms, each of which uses the output from a single partial ...one sense, as do the simulated annealing , ... See full document
30
Unsupervised Word Sense Disambiguation Using Neighborhood Knowledge
... ambiguous word influences WSD performance, we conduct experiment with different values for within-sentence window size n 1 and cross-sentence window size n 2 ...ambiguous word have the best ... See full document
10
Improving Word Sense Disambiguation with Linguistic Knowledge from a Sense Annotated Treebank
... of knowledge-based and supervised systems for WSD, which demonstrates that the two ap- proaches can boost one another, due to the funda- mentally different types of knowledge they utilise (paradigmatic ...a ... See full document
8
Domain Adaptation with Active Learning for Word Sense Disambiguation
... predominant sense, or most frequent sense (MFS), of each noun in our WSJ test data perfectly, and we assign this most frequent sense to each noun in the test data, we will have achieved an accuracy ... See full document
8
Unsupervised, Knowledge Free, and Interpretable Word Sense Disambiguation
... available word sense disambiguation system that is unsupervised, knowledge-free, and interpretable at the same ...of word and super sense inventories from a text ...The ... See full document
6
GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge
... lexical knowledge. The gloss, which defines a word sense meaning, is first utilized in Lesk algorithm (Lesk, 1986) and then widely taken into account in many other approaches (Banerjee and Pedersen, ... See full document
6
Word Sense Disambiguation by Learning from Unlabeled Data
... In a series of experiments on word sense disambiguation of Korean nouns we observed that the accuracy is improved up to 20.2% using only 32% of labeled data.. This implies, the learning [r] ... See full document
8
Experiments on Active Learning for Croatian Word Sense Disambiguation
... fort, rendering such approaches particularly cost- ineffective for smaller languages. On the other hand, supervised approaches do not rely on lexi- cal resources and generally outperform knowledge- based ... See full document
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