Sökning: "Natural Language Processing"

Visar resultat 1 - 5 av 127 uppsatser innehållade orden Natural Language Processing.

1. 1. Domain similarity metrics for predicting transfer learning performance

   Master-uppsats, Linköpings universitet/Interaktiva och kognitiva system

   Författare :Jesper Bäck; [2019]
   Nyckelord :nlp.natural language processing; machine learning; transfer learning; similarity metrics; similarity; predict; performance;

   Sammanfattning : The lack of training data is a common problem in machine learning. One solution to thisproblem is to use transfer learning to remove or reduce the requirement of training data.Selecting datasets for transfer learning can be difficult however. LÄS MER

3. 2. Study of Semi-supervised Deep Learning Methods on Human Activity Recognition Tasks

   Master-uppsats, KTH/Robotik, perception och lärande, RPL

   Författare :Shiping Song; [2019]
   Nyckelord :Semi-supervised learning; Sequence learning; Human activity recognization; DeepConvLSTM; Seq2seq model;

   Sammanfattning : This project focuses on semi-supervised human activity recognition (HAR) tasks, in which the inputs are partly labeled time series data acquired from sensors such as accelerometer data, and the outputs are predefined human activities. Most state-of-the-art existing work in HAR area is supervised now, which relies on fully labeled datasets. LÄS MER

4. 3. Dealing with word ambiguity in NLP. Building appropriate sense representations for Danish sense tagging by combining word embeddings with wordnet senses

   Master-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori

   Författare :Ida Rørmann Olsen; [2018-12-13]
   Nyckelord :sense embeddings; wordnet; word2vec; word sense disambiguation; clustering; machine learning; supervised WSD;

   Sammanfattning : This thesis describes an approach to handle word sense in natural language processing. If we want language technologies to handle word ambiguity, then machines need proper sense representations. LÄS MER

5. 4. Exploit Unlabeled Data with Language Model for Text Classification. Comparison of four unsupervised learning models

   Master-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori

   Författare :Sung-Min Yang; [2018-10-29]
   Nyckelord :Text classification; Semi-supervised learning; Unsupervised learning; Transfer learning; Natural Language Processing;

   Sammanfattning : Within a situation where Semi-Supervised Learning (SSL) is available to exploit unlabeled data, this paper shows that Language Model (LM) outperforms the three models in text classification, which three models are based on Term-Frequency Inverse Document Frequency (Tf-idf) and two pre-trained word vectors. The experimental results show that the LM outperforms the other three unsupervised learning models whether the task is easy or difficult, which the difficult task consists of imbalanced data. LÄS MER

7. 5. Deep Neural Networks for Inverse De-Identification of Medical Case Narratives in Reports of Suspected Adverse Drug Reactions

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Eva-Lisa Meldau; [2018]
   Nyckelord :De-Identification; Deep Learning; Recurrent Neural Networks; Natural Language Processing; Pharmacovigilance; Medical Language Processing; Privacy Protection; Adverse Drug Reactions;

   Sammanfattning : Medical research requires detailed and accurate information on individual patients. This is especially so in the context of pharmacovigilance which amongst others seeks to identify previously unknown adverse drug reactions. LÄS MER