Search for dissertations about: "Word Embeddings"

Showing result 1 - 5 of 14 swedish dissertations containing the words Word Embeddings.

  2. 1. Principal Word Vectors

    Author : Ali Basirat; Joakim Nivre; Hinrich Schütze; Uppsala universitet; []
    Keywords : HUMANIORA; HUMANITIES; NATURVETENSKAP; NATURAL SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; word; context; word embedding; principal component analysis; PCA; sparse matrix; singular value decomposition; SVD; entropy;

    Abstract : Word embedding is a technique for associating the words of a language with real-valued vectors, enabling us to use algebraic methods to reason about their semantic and grammatical properties. This thesis introduces a word embedding method called principal word embedding, which makes use of principal component analysis (PCA) to train a set of word embeddings for words of a language. READ MORE

  4. 2. Splitting rocks: Learning word sense representations from corpora and lexica

    Author : Luis Nieto Piña; Göteborgs universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; language technology; natural language processing; distributional models; semantic representations; distributed representations; word senses; embeddings; word sense disambiguation; linguistic resources; corpus; lexicon; machine learning; neural networks;

    Abstract : The representation of written language semantics is a central problem of language technology and a crucial component of many natural language processing applications, from part-of-speech tagging to text summarization. These representations of linguistic units, such as words or sentences, allow computer applications that work with language to process and manipulate the meaning of text. READ MORE

  5. 3. Word Vector Representations using Shallow Neural Networks

    Author : Oluwatosin Adewumi; Marcus Liwicki; Marco Kuhlmann; Luleå tekniska universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Word vectors; NLP; Neural networks; Embeddings; Maskininlärning; Machine Learning;

    Abstract : This work highlights some important factors for consideration when developing word vector representations and data-driven conversational systems. The neural network methods for creating word embeddings have gained more prominence than their older, count-based counterparts. READ MORE

  6. 4. Word Sense Embedded in Geometric Spaces - From Induction to Applications using Machine Learning

    Author : Mikael Kågebäck; Chalmers tekniska högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; HUMANIORA; HUMANITIES; NATURVETENSKAP; NATURAL SCIENCES; word sense induction; word sense disambiguation; word embeddings; extractive summarisation; neural networks; deep learning; natural language procsessing; reinforcement learning;

    Abstract : Words are not detached individuals but part of a beautiful interconnected web of related concepts, and to capture the full complexity of this web they need to be represented in a way that encapsulates all the semantic and syntactic facets of the language. Further, to enable computational processing they need to be expressed in a consistent manner so that similar properties are encoded in a similar way. READ MORE

  7. 5. A typology of classifiers and gender : From description to computation

    Author : Marc Tang; Michael Dunn; Christine Lamarre; Sebastian Fedden; Uppsala universitet; []
    Keywords : HUMANIORA; HUMANITIES; NATURVETENSKAP; NATURAL SCIENCES; Classifiers; Gender; Nominal classification; Functions; Random Forests; Phylogeny; Word Embeddings; Neural Networks; Linguistics; Lingvistik;

    Abstract : Categorization is one the most relevant tasks realized by humans during their life, as we consistently need to categorize the things and experience that we encounter. Such need is reflected in language via various mechanisms, the most prominent being nominal classification systems (e.g. READ MORE