[PDF] Top 20 Word Sense Induction: Triplet Based Clustering and Automatic Evaluation
Has 10000 "Word Sense Induction: Triplet Based Clustering and Automatic Evaluation" found on our website. Below are the top 20 most common "Word Sense Induction: Triplet Based Clustering and Automatic Evaluation".
Word Sense Induction: Triplet Based Clustering and Automatic Evaluation
... is based on the one sense per collocation observation (Gale et ...for word pairs in a predicate-argument relationship than for arbitrary associations at equivalent distance, ...(target word ... See full document
8
Measuring the Impact of Sense Similarity on Word Sense Induction
... two evaluation for WSI approaches and examined the performance of a wide range of ...for clustering-based WSI approaches: sense discrimi- nation degrades notably as the sense ... See full document
11
Fine Grained Word Sense Disambiguation Based on Parallel Corpora, Word Alignment, Word Clustering and Aligned Wordnets
... Word Sense Disambiguation (WSD) is well- known as one of the more difficult problems in the field of natural language processing, as noted in (Gale et al, 1992; Kilgarriff, 1997; Ide and Véronis, 1998), and ... See full document
7
Word Sense Induction Using Lexical Chain based Hypergraph Model
... Word Sense Induction is a task of automatically finding word senses from large scale ...target word occurs and hyperedges represent high- er-order semantic relatedness among ...chain ... See full document
11
Improved Estimation of Entropy for Evaluation of Word Sense Induction
... WSI evaluation and argued that main drawbacks of these approaches, such as the preference for the systems predicting richer clusterings or assigning the top score to the 1-cluster-per-instance baseline, are caused ... See full document
16
Latent Semantic Word Sense Induction and Disambiguation
... a word on a per-word basis, i.e. the different senses for each word are determined ...particular word, and those con- texts are grouped into a number of clusters, repre- senting the different ... See full document
10
Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph based Word Sense Induction
... a word are represented by the closest monosemous terms on the WordNet graph, according to Personal- ized PageRank (Haveliwala, 2002) applied to the WordNet ...different clustering algorithms on two data ... See full document
10
Clustering and Diversifying Web Search Results with Graph Based Word Sense Induction
... result clustering outperforms all other approaches across all evaluation measures on the two corpora, except for KeySRC and the singleton baseline when using the F1 ...algorithms based on graph ... See full document
46
Taxonomy Learning Using Word Sense Induction
... get word in a given ...The evaluation framework defines two types of as- sessment, i.e. evaluation in: (1) a clustering and (2) a WSD ...setting. Based on this evaluation, we se- ... See full document
9
Chinese Word Sense Induction based on Hierarchical Clustering Algorithm
... Sense induction seeks to automatically identify word senses of polysemous words encountered in a ...Unsupervised word sense induction can be viewed as a clustering ... See full document
5
Triplet Based Chinese Word Sense Induction
... Sense induction is typically treated as a clustering problem, by considering their co- occurring contexts, the instances of a target word are partitioned into ...get word is ... See full document
5
AutoSense Model for Word Sense Induction
... Word sense induction (WSI), or the task of automatically dis- covering multiple senses or meanings of a word, has three main challenges: domain adaptability, novel sense detection, and ... See full document
8
Nonparametric Bayesian Word Sense Induction
... the sense- specification problem, rather than eking out further improvements in the base WSI evaluation measure, we chose to compare a standard LDA model to HDP, both strictly using a 10 word ... See full document
5
Evaluating Unsupervised Ensembles when applied to Word Sense Induction
... of Word Sense Induction with a framework for combining diverse feature spaces and cluster- ing ...existing Word Sense In- duction ... See full document
6
Naive Bayes Word Sense Induction
... target word with the most frequent sense (MFS). UoY runs a clustering algorithm on a graph with words as nodes and co-occurrences between words as edges (Korkontzelos and Manandhar, ...Agglomerate ... See full document
5
Word Sense Induction by Community Detection
... to sense-specific ...the sense inventory; selecting a commu- nity solution purely based on the graph’s structure may not capture the correct sense distinctions, ei- ther having communities ... See full document
5
Using Wikipedia for Automatic Word Sense Disambiguation
... the sense distinctions identified in Wikipedia are fewer and typically coarser than those found in ...per word found in Wikipedia. This is partly due to a differ- ent sense coverage and distribution ... See full document
8
Automatic Domain Assignment for Word Sense Alignment
... of sense de- scriptions of the words ...basic sense descriptions with addi- tional information such as hypernyms, synonyms and domain or category ... See full document
5
Word Sense Induction using Cluster Ensemble
... Domeniconi et al.(2004) proposed an Locally Adaptive Clustering algorithm (LAC), which discovers clusters in subspaces spanned by different combinations of dimensions via local weightings of features. Dimensions ... See full document
8
Word Sense Ambiguation: Clustering Related Senses
... WORD SENSE AMBIGUATION CLUSTERING RELATED SENSES W O R D S E N S E A M B I G U A T I O N C L U S T E R I N G R E L A T E D S E N S E S William B Dolan Microsoft Research billdol @ microsoft corn A b s[.] ... See full document
5
Related subjects