[PDF] Top 20 Contextual Word Similarity and Estimation From Sparse Data
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Contextual Word Similarity and Estimation From Sparse Data
... The similarity based estimation method was used to estimate the expected frequency of unobserved cooccurrence pairs, in cases where none of the alternative pairs occurred in the corpus e[r] ... See full document
8
Kernel density construction using orthogonal forward regression
... on sparse data modeling [4],[5], we propose an ef- ficient algorithm for sparse kernel density estimation using an orthogonal forward re- gression (OFR) based on leave-one-out (LOO) test score ... See full document
6
Improving sparse word similarity models with asymmetric measures
... to word similarity becomes clear when we consider that for many applications, word similarity measures need to be well-defined when comparing very fre- quent words with infrequent ...a ... See full document
6
A Rank Based Similarity Metric for Word Embeddings
... little similarity about them), as opposed to ‘gen- uine’ semantic similarity ...that similarity estimation alone does not constitute a strong benchmark, as the inter-annotator agree- ment is ... See full document
6
Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets
... on sparse data sets depreciates their performance, results from pre-trained and re- trained RNTN are presented to further support this ...learning word embeddings, resulting word ... See full document
8
A Benchmark Corpus of English Misspellings and a Minimally supervised Model for Spelling Correction
... clinical data (Table 7). Orthographic similarity is the most useful fea- ture, just as it is in the TOEFL-Spell data set, and removing it results in a very big performance drop (almost 30 ... See full document
11
A Synonym Contextual-based Process for Handling Word Similarity in Malay Sentence
... preparing data for our requirements, we have been pointed with a few worthwhile books such as [4,5,9] to get primary understanding on the essential requirements, specifically in studying syntax and grammar ... See full document
5
Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence
... training data, which originates from a tex- tual entailment corpus having unique properties such as disparities in the lengths of the input sentences and a directional nature of their relationship ... See full document
12
Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes
... LexSub data (10 instances x 56 lem- mas) has additionally been annotated with graded pairwise Usim judgments (Erk et ...scores from Usim annotations that denote how easy it is to parti- tion a lemma’s ... See full document
13
Text Similarity Estimation Based on Word Embeddings and Matrix Norms for Targeted Marketing
... Word2Vec word embeddings were trained on the German Wikipedia (dump originating from 20 February 2017) merged with a Frankfurter Rundschau newspaper Corpus and 34 249 articles of the news journal 20 minutes ... See full document
10
Walk based Computation of Contextual Word Similarity
... the similarity of structured data is to count shared substruc- tures with the so-called convolution kernels (Haussler, 1999; Gärtner, ...the similarity between words in parse graphs, we use a ... See full document
16
Word similarity using constructions as contextual features
... of contextual features for word simi- larity detection based on the notion of lexico- grammatical ...semantic similarity of words attested in selected positions, we extend the notion of selection ... See full document
9
Sparse Overcomplete Word Vector Representations
... on similarity (rather than ...cosine similarity between the vectors of two words forming a test item and re- port Spearman’s rank correlation coefficient (My- ers and Well, 1995) between the rankings pro- ... See full document
10
An Estimation based Automatic Vehicle Location System for Public Transport Vehicles
... spatial data layer. The data layer is distributed across these iTransIT systems, with each system implementing the subset of the overall layer that is relevant to its ...the data layer may actually ... See full document
7
Querying Word Embeddings for Similarity and Relatedness
... available similarity/relatedness data is the explicit instruc- tion of participants to pay attention to one aspect of word relations and not the ...how word embedings should be used to measure ... See full document
10
Improving Distributional Similarity with Lessons Learned from Word Embeddings
... tokens from the corpus before creating context ...new word-context pairs that did not exist in the original corpus with the same window ...a word and its con- text is well known to be an effective ... See full document
16
Improving Word Alignment using Word Similarity
... obtained from a monolingual the- saurus, in which humans manually provide sub- jective evaluation for word similarity probabilities, but an automatic method would be ...the word ... See full document
6
Improving Statistical MT through Morphological Analysis
... pora, sparse data is a serious issue when estimating the parameters of the translation ...reduce data sparseness and increase similarity between lan- guages, thus improving the quality of ... See full document
8
Contextual Dependencies in Unsupervised Word Segmentation
... that word segmentation could be improved by taking into account dependencies between ...each word has a different distribution over the words that follow it, but all these distributions are ... See full document
8
Joint state-parameter estimation of a nonlinear stochastic energy balance model from sparse noisy data
... Acknowledgements. The authors thank Colin Grudzien and the other reviewer for helpful comments. This research started in a working group supported by the Statistical and Applied Mathematical Sciences Institute (SAMSI). ... See full document
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