Add to ORKGThis thesis deals with semantic similarity of words. It describes and compares existing models that are currently used for this purpose. It discusses the design and implementation of the system for corpus preprocessing, semantic modelling and retrieval of semantically related words. The system that has been created supports the use of distributional semantic models Word2vec, FastText and Glove
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...
This thesis describes a clustering approach to automatically inferring soft semantic classes and cha...
Word Space Models provide a convenient way of modelling word meaning in terms of a word’s contexts i...
This Bachelor's thesis deals with the semantic similarity of words . It describes the design and the...
This bachelor's thesis deals with the design and implementation of a modular system focused on seman...
Summarization: In this thesis, motivated by evidences in psycholinguistics and cognition, we propose...
SenseClusters is a freely available intelligent system that clusters together similar contexts in na...
The goal of this thesis is processing knowledge about Automatic Term Recognition and methods of comp...
Abstract. Semantic relatedness refers to the degree to which two concepts or words are related. Huma...
Abstract- Usually in text mining techniques the basic measures like term frequency of a term (word o...
Abstract. A specific sense of a word can be determined by collocation of the words gathered from the...
Distributional Semantic Models (DSM) are growing in popularity in Computational Linguistics. DSM use...
This paper describes the use of clustering at three stages within a larger research effort to identi...
SenseClusters is a freely available word sense discrimination system that takes a purely unsupervise...
This thesis describes a clustering approach to automatically inferring soft semantic classes and cha...
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...
This thesis describes a clustering approach to automatically inferring soft semantic classes and cha...
Word Space Models provide a convenient way of modelling word meaning in terms of a word’s contexts i...
This Bachelor's thesis deals with the semantic similarity of words . It describes the design and the...
This bachelor's thesis deals with the design and implementation of a modular system focused on seman...
Summarization: In this thesis, motivated by evidences in psycholinguistics and cognition, we propose...
SenseClusters is a freely available intelligent system that clusters together similar contexts in na...
The goal of this thesis is processing knowledge about Automatic Term Recognition and methods of comp...
Abstract. Semantic relatedness refers to the degree to which two concepts or words are related. Huma...
Abstract- Usually in text mining techniques the basic measures like term frequency of a term (word o...
Abstract. A specific sense of a word can be determined by collocation of the words gathered from the...
Distributional Semantic Models (DSM) are growing in popularity in Computational Linguistics. DSM use...
This paper describes the use of clustering at three stages within a larger research effort to identi...
SenseClusters is a freely available word sense discrimination system that takes a purely unsupervise...
This thesis describes a clustering approach to automatically inferring soft semantic classes and cha...
This paper describes an unsupervised graph-based method for word sense disambiguation, and presents ...
This thesis describes a clustering approach to automatically inferring soft semantic classes and cha...
Word Space Models provide a convenient way of modelling word meaning in terms of a word’s contexts i...