[PDF] Top 20 One Distributional Memory, Many Semantic Spaces
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One Distributional Memory, Many Semantic Spaces
... We test on the two datasets of human judgments about the plausibility of nouns as arguments (ei- ther subjects or objects) of verbs used in Pad´o et al. (2007), one (McRae) consisting of 100 noun- verb pairs rated ... See full document
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Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross Lingual Constraints
... Task-oriented dialogue systems help users achieve goals such as making travel reservations or finding restaurants. In slot-based systems, application do- mains are defined by ontologies which enumerate the goals that ... See full document
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Building a shared world: mapping distributional to model theoretic semantic spaces
... standard distributional se- mantic space onto a set-theoretic ...between distributional information and vecto- rial concept representations in which dimen- sions are predicates and weights are gener- alised ... See full document
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Corpus Driven Terminology Development: Populating Swedish SNOMED CT with Synonyms Extracted from Electronic Health Records
... more semantic relations, and indeed more synonyms, are extracted by the Unigram Word Space than the Multiword Term ...a distributional framework and to handle semantic composition – ...identify ... See full document
9
Building and Evaluating a Distributional Memory for Croatian
... jects of transitive verbs) and Sub intr (subject of intransitive verbs). The motivation for this is better modeling of verb semantics by capturing diathe- sis alternations. In particular, for many Croatian verbs ... See full document
6
Semantic Classification with Distributional Kernels
... why distributional kernels per- form better than the standard linear and Gaussian ...kernels. One answer might be that just as infor- mation theory provides the “correct” notion of in- formation for ... See full document
8
Inference with Distributional Semantic Models
... was one-way ...of semantic spaces (Section ...of spaces in which the measure was able to predict membership direction significantly better than chance (binomial test, p < ...NMF) ... See full document
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Computing Semantic Compositionality in Distributional Semantics
... to semantic compositionality in computational lin- guistics based on the combination of Distributional Semantics and supervised Machine ...brief, distributional semantic spaces ... See full document
10
Affordances in Grounded Language Learning
... conceptual spaces generated by the representa- tional techniques described above, we first ex- tract the word-vectors corresponding to our vocab- ulary from the word2vec distributional semantic model ... See full document
6
Towards a Distributional Model of Semantic Complexity
... The semantic complexity model we have proposed in this paper is strongly inspired by the general cognitive principles of the MUC ...a memory component, consisting of a distributional subset of GEK, ... See full document
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An Automated Complex Word Identification from Text: A Survey
... Wikipedia corpus by (Kauchak, 2013). The CW corpus contains 731 simple English sentences in which one complex word is substituted by Wikipedia editors. The second data set Lex M Turk is commonly used for CWI is ... See full document
6
tESA: a distributional measure for calculating semantic relatedness
... Background: Semantic relatedness is a measure that quantifies the strength of a semantic link between two ...Approximating semantic relatedness between texts and concepts represented by these texts ... See full document
14
How we BLESSed distributional semantic evaluation
... promise: Semantic relations are not limited to tax- onomic types and also include attributes and events strongly related to a concept, but in these cases we have resorted to underspecification, rather than com- ... See full document
10
CCG Categories for Distributional Semantic Models
... The distributional semantic approach is based on the idea that the meaning of a word relies heavily on its ...based Distributional Semantic Models (DSMs) have been tested against several tasks ... See full document
8
Squibs: When the Whole Is Not Greater Than the Combination of Its Parts: A “Decompositional” Look at Compositional Distributional Semantics
... compositional distributional semantic models (CDSMs) estimate degrees of seman- tic similarity (or, more generally, relatedness) between two phrases: A good CDSM might tell us that green bird is closer to ... See full document
10
Measuring semantic content in distributional vectors
... in distributional semantics as a representation of lex- ical ...a distributional semantic space, for instance, the word ‘cat’ may be close to ‘dog’ or to ‘tiger’, and its vector might have high ... See full document
6
Many Perceptions, One Landscape
... Given that the primary role of the case study was to test the usefulness of the Cultural Values Model in understanding landscape significance in an integrated way, the [r] ... See full document
22
Semantic transparency: challenges for distributional semantics
... ity: in each case, the more literal the constituent, the more literal the compound. Surprisingly, however, the other constituent-based variables remain significant even in the presence of the constituent literality ... See full document
10
Many Languages, One Parser
... We train one multilingual model for depen- dency parsing and use it to parse sentences in several languages. The parsing model uses (i) multilingual word clusters and em- beddings; (ii) token-level language ... See full document
14
One Land, Many Nations
... The postmemories of these survivors, who were children or teenagers at the time of the Partition of Punjab in 1947, folded in the villages flanking the Indus in a domestic geography of sailing in a boat from the natal ... See full document
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