Vector Space
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... While vector space representations for indi- vidual words are well-understood, there remains much uncertainty about how to compose vector space representations for phrases out of their com- ...
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A Vector Space for Distributional Semantics for Entailment
... These noun-noun word pairs include positive hy- ponymy pairs, plus negative pairs consisting of some other hyponymy pairs reversed, some pairs in other semantic relations, and some random pairs. Their selection is ...
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Vector Space semi-Cayley Graphs
... dimensional vector space over the field of real numbers, then the degree of each vertex is equal to the ...dimensional vector space with a basis which does not contain any element that is ...
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Interval-valued Fuzzy Vector Space
... fuzzy vector space, after that many researchers investigated its properties and characteristics [1, 2, 11, 12, 13, 14, ...fuzzy vector space (IVFVS) with respect to ...
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Lattices Associated with a Finite Vector Space
... The special lattices of rough algebras were discussed in [3]. The lattices generated by orbits of subspaces un- der finite (singular) classical groups were discussed in [4] [5]. Wang et al. [6]-[8] constructed some ...
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Semigroups of singular endomorphisms of vector space
... the subsemigroup generated by E^ , I have considered the subsemigroup generated by E^\{l) where I is the identity mapping. This restric tion is of trivial effect since <E^> = <E^\{I}> U {i} . it has already ...
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Traversing Knowledge Graphs in Vector Space
... We have two key empirical findings: First, we show that compositional training enables us to answer path queries up to at least length 5 by substantially reducing cascading errors present in the base vector ...
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10. FUZZY ALGEBRA AND FUZZY VECTOR SPACE
... The concepts of fuzzy set was introduced by Zadeh [6],and the notion of fuzzy vector space was defined and established by KATSARAS,A.K and LIU,D.B [2]. Using the definition of fuzzy vector ...
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Multi Prototype Vector Space Models of Word Meaning
... We presented a resource-light model for vector- space word meaning that represents words as col- lections of prototype vectors, naturally accounting for lexical ambiguity. The multi-prototype approach uses ...
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Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality
... word vector space models, they are severely limited since they do not capture compositionality, the important quality of natural language that allows speakers to determine the meaning of a longer expression ...
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Vector Space Models for Phrase based Machine Translation
... This paper investigates the application of vector space models (VSMs) to the standard phrase-based machine translation pipeline. VSMs are models based on continuous word representations embed- ded in a ...
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A Systematic Study of Semantic Vector Space Model Parameters
... Vector space models (VSMs) represent the mean- ings of lexical items as vectors in a “semantic space”. The benefit of VSMs is that they can eas- ily be manipulated using linear algebra, allowing a ...
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Extension of n dimensional Euclidean vector space En over ℝ to pseudo fuzzy vector space over Fp1(1)
... fuzzy vector space is a pair E = (E,µ) , where E is a vector space and µ : E → [ 0 , 1 ] with the property that, for all a,b ∈ R and x,y ∈ E , we have µ(ax + by) ≥ µ(x)∧ µ(y) ...a ...
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Lexical Transfer Using a Vector Space Model
... Building a bilingual dictionary for transfer in a machine translation system is conventionally done by hand and is very time-consuming. In order to overcome this bottleneck, we propose a new mechanism for lexical ...
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Taking Antonymy Mask off in Vector Space
... by vector cosine (Turney and Pantel, ...the vector space typically include hypernyms like building, co-hyponyms like house, meronyms like brick, antonyms like shack, together with other semantically ...
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Vector Space Models for Scientific Document Summarization
... Our vector space model uses the TF representation of the text and a low rank approximation of the term-sentence matrix using ...TF vector space model is a good basic model, but we showed that ...
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Neural Vector Conceptualization for Word Vector Space Interpretation
... word vector spaces are consid- ered hard to interpret which hinders the under- standing of natural language processing (NLP) ...original vector space and is capable of learning non-linear relations ...
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Looking for Hyponyms in Vector Space
... BalAPInc, a measure described by Kotlerman et al. (2010), combines the APInc score with Lin similarity by taking their geometric average. The APInc measure finds the proportion of shared fea- tures relative to the ...
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Vector Space-Groupoids
... a vector space-groupoid called the vector space-groupoid with a single unit associated to V ...each vector space V has a structure of vector space −{ e }− ...
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Applicative structure in vector space models
... Section 2 offers a method to treat antonymy in continuous vector space models (CVSMs). Sec- tion 3 describes a new embedding, 4lang, obtained by spectral clustering from the definitional frame- work of the ...
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