[PDF] Top 20 Determining Compositionality of Word Expressions Using Word Space Models
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Determining Compositionality of Word Expressions Using Word Space Models
... in compositionality is motivated by the hypothesis that a special treatment of se- mantically non-compositional expressions can im- prove results in various Natural Language Process- ing (NPL) tasks, as ... See full document
9
Determining Compositionality of Expresssions Using Various Word Space Models and Methods
... of expressions different from types; Measures could be ...of expressions (Evert, ...candidate expressions occurring in some smaller ...non-compositional expressions and to be provided with an ... See full document
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A Word Embedding Approach to Predicting the Compositionality of Multiword Expressions
... two models, is able to learn multiple em- beddings per target word (or ...three models, we first greedily pre-tokenise the corpus to represent each MWE as a single token, similarly to Baldwin et ... See full document
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Exemplar Based Word Space Model for Compositionality Detection: Shared Task System Description
... Table 2 displays Spearman ρ and Kendalls τ corre- lation scores of all the models. TotPrd stands for the total number of predictions. Rand-Base is the baseline system which randomly assigns a compo- sitionality ... See full document
7
Alternative measures of word relatedness in distributional semantics
... tor space models, so there is hope for improve- ...tic compositionality, since our method can be ex- tended from measuring word-word semantic relat- edness to evaluating phrasal ... See full document
5
Additive Compositionality of Word Vectors
... about word vectors and how they are used in existing word embedding ...vector space (Arora et al., 2016). Second, we describe sub-sampling, a word frequency bal- ancing method to increase ... See full document
10
Tree Rewriting Models of Multi Word Expressions
... In particular, this conversion results in a subset of tree-rewriting systems in which each (binary) branch of every elementary tree must have exactly one argu- ment position and one non-argument position among its two ... See full document
6
Factoring Ambiguity out of the Prediction of Compositionality for German Multi Word Expressions
... mantic models (DSMs), ...the compositionality prediction, DSMs repre- sent the meanings of the MWEs and their con- stituents by distributional vectors, and the sim- ilarity of a compound–constituent vector ... See full document
7
Detecting Compositionality of Multi Word Expressions using Nearest Neighbours in Vector Space Models
... neighbours, which means that the neighbours have to be ranked. An obvious ranking method is to use the frequency with which each neighbour co-occurs with the other constituent(s) of the same phrase. For example, for all ... See full document
6
Relative Compositionality of Multi word Expressions: A Study of Verb Noun (V N) Collocations
... (MI3), Log-Log [17], etc., have been proposed. These measures try to quan- tify the association of the two words but do not talk about quantifying the non-compositionality of MWEs. Dekang Lin proposes a way to ... See full document
12
Determining the Unithood of Word Sequences Using a Probabilistic Approach
... Most research related to unithood were con- ducted as part of a larger effort for the deter- mination of termhood. Consequently, nov- elties are rare in this small sub-field of term extraction. In addition, existing work ... See full document
8
What Is Word Meaning, Really? (And How Can Distributional Models Help Us Describe It?)
... in space, namely the vector for contract, and to trig- ger the inference rule for an occurrence of catch if it is close enough to the attachment ...a word sense not as a point but as a region in vector ... See full document
10
Modeling Word Meaning: Distributional Semantics and the Corpus Quality Quantity Trade Off
... The Google Web corpus (Web) (Brants, 2006) contains n-grams of length up to 5 generated from publicly accessible Web pages. The Google Books dataset (Books) containing n-grams up to length 5 is extracted from a ... See full document
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Centroid based Text Summarization through Compositionality of Word Embeddings
... the word embeddings (Mikolov et ...of word embed- dings with a fair comparison to the BOW represen- tation by limiting, as much as possible, the param- eters and the complexity of the ... See full document
10
An Approach to Take Multi Word Expressions
... idiomatic expressions, such as take one for the ...such expressions, an efficient way for increasing coverage is ...multi- word expressions to the PropBank lexicon in an effective yet ... See full document
5
Determining the Difficulty of Word Sense Disambiguation
... Automatic processing of biomedical documents is made difficult by the fact that many of the terms they contain are ambiguous. Word Sense Disambiguation (WSD) systems attempt to resolve these ambiguities and ... See full document
9
Representation and processing of multi word expressions in the brain
... We interpret the early positivity observed in highly constraining contexts as the manifestation of template matching mechanisms, wherein the target sequence, being highly predictable, activates a template in the lexicon ... See full document
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Stepwise Mining of Multi Word Expressions in Hindi
... Samaas (N+N, A+N) and Sandhi (means joining or fusion of words) are Hindi grammatical con- structs at the morphological level and are borrowed concepts from Sanskrit. In Samaas, while combin- ing the two words, the ... See full document
6
Querying Multi word Expressions Annotation with CQL
... Concordance systems (in our paper KonText and NoSke, but also their ancestors such as the Sketch Engine, and the IMS Open Corpus Workbench) for exploring corpora using CQL queries are well known tools among ... See full document
7
Regularizing Mono and Bi Word Models for Word Alignment
... the models IBM-1 and HMM, then generalize to models we term Bi-word models, where each target word can be aligned to up to two source ...tasks, using EM and projected gra- dient ... See full document
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