Vector Representation
Related Papers
Part-of-Speech Induction From Scratch
This paper presents a method for inducing the parts of speech of a language and part- of-speech labels for individual words from a large text corpus. Vector representations for the …...
Document Representation in Natural Language Text Retrieval
In information retrieval, the content of a document may be represented as a collection of terms: words, stems, phrases, or other units derived or inferred from the text of the …...
Cross-Lingual Text Filtering Based on Text Concepts and kNN
This paper presents the model that can be used to filter the texts which the user is interested in from a large scale of source texts in Chinese or in …...
Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces
This paper systematically compares unsuper- vised word sense discrimination techniques that cluster instances of a target word that oc- cur in raw text using both vector and similarity spaces. The …...
Separating Disambiguation from Composition in Distributional Semantics
Most compositional-distributional models of meaning are based on ambiguous vec- tor representations, where all the senses of a word are fused into the same vec- tor. This paper provides evidence …...
The Role of Syntax in Vector Space Models of Compositional Semantics
Modelling the compositional process by which the meaning of an utterance arises from the meaning of its parts is a funda- mental task of Natural Language Process- ing. In this …...
Common Space Embedding of Primal-Dual Relation Semantic Spaces
Explicit continuous vector representation such as vector representation of words, phrases, etc. has been proven effective for various NLP tasks. This paper proposes a novel method of constructing such vector …...
Improving Vector Space Word Representations Using Multilingual Correlation
The distributional hypothesis of Harris (1954), according to which the meaning of words is evidenced by the contexts they occur in, has motivated several effec- tive techniques for obtaining vector …...
Classifying Idiomatic and Literal Expressions Using Vector Space Representations
We describe an algorithm for automatic classification of idiomatic and literal ex- pressions. Our starting point is that idioms and literal expressions occur in different contexts. Idioms tend to violate …...
Assessing the Potential of Metaphoricity of verbs using corpus data
AbstractThe paper investigates the relation between metaphoricity and distributional characteristics of verbs, introducing POM, a corpus-derived index that can be used to define the upper bound of metaphoricity of any …...
Rotated Word Vector Representations and their Interpretability
AbstractVector representation of words improves performance in various NLP tasks, but the high dimensional word vectors are very difficult to interpret. We apply several rotation algorithms to the vector representation …...
Learning to Rank Question-Answer Pairs Using Hierarchical Recurrent Encoder with Latent Topic Clustering
AbstractIn this paper, we propose a novel end-to-end neural architecture for ranking candidate answers, that adapts a hierarchical recurrent neural network and a latent topic clustering module. With our proposed …...
Affect-Driven Dialog Generation
AbstractThe majority of current systems for end-to-end dialog generation focus on response quality without an explicit control over the affective content of the responses. In this paper, we present an …...
Weakly Supervised Pre-Training for Multi-Hop Retriever
In multi-hop QA, answering complex ques- tions entails iterative document retrieval for finding the missing entity of the question. The main steps of this process are sub-question detection, document retrieval …...