Sökning: "Natural Language Processing"
Visar resultat 1 - 5 av 122 uppsatser innehållade orden Natural Language Processing.
1. Dealing with word ambiguity in NLP. Building appropriate sense representations for Danish sense tagging by combining word embeddings with wordnet sensesMaster-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori
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
2. Exploit Unlabeled Data with Language Model for Text Classification. Comparison of four unsupervised learning modelsMaster-uppsats, Göteborgs universitet/Institutionen för filosofi, lingvistikoch vetenskapsteori
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
3. Deep Neural Networks for Inverse De-Identification of Medical Case Narratives in Reports of Suspected Adverse Drug ReactionsMaster-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
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
- Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)
Sammanfattning : Short text classification has become an important task for the Natural Language Processing (NLP) community due to the rapidly growing amount of tweets, search queries, short reviews and descriptions in different contexts such as e-commerce, social media and internal Enterprise Resource Planning (ERP) systems. The brevity and sparsity of such text data represent challenges to build accurate classification models. LÄS MER
- Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi
Sammanfattning : Spelling normalization is the task to normalize non-standard words into standard words in texts, resulting in a decrease in out-of-vocabulary (OOV) words in texts for natural language processing (NLP) tasks such as information retrieval, machine translation, and opinion mining, improving the performance of various NLP applications on normalized texts. In this thesis, we explore diﬀerent methods for spelling normalization of English student writings including traditional Levenshtein edit distance comparison, phonetic similarity comparison, character-based Statistical Machine Translation (SMT) and character-based Neural Machine Translation (NMT) methods. LÄS MER