Sökning: "Natural Language Processing"
Visar resultat 1 - 5 av 176 uppsatser innehållade orden Natural Language Processing.
- Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik
Sammanfattning : In recent years, fake news has become a pervasive reality of global news consumption.While research on fake news detection is ongoing, smaller languages such as Swedishare often left exposed by an under-representation in research. LÄS MER
- Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för datalogi
Sammanfattning : Sentiment analysis is a field within the area of natural language processing that studies the sentiment of human written text. Within sentiment analysis, sentiment classification is a research area that has been of growing interest since the advent of digital social-media platforms, concerned with the classification of the subjective information in text data. LÄS MER
- Master-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)
Sammanfattning : We live in a time where software is used everywhere. It is used even for creating other software by helping developers with writing or generating new code. To do this properly, metrics to measure software quality are being used to evaluate the final code. However, they are sometimes too costly to compute, or simply don't have the expected effect. LÄS MER
- Master-uppsats, KTH/Matematisk statistik
Sammanfattning : This thesis work takes place at the Emerging Technologies department of Volvo Construction Equipment(CE), in the context of a larger project which involves several students. The focus is a mobile robot built by Volvo for testing some AI features such as Decision Making, Natural Language Processing, Speech Recognition, Object Detection. LÄS MER
5. Emotion Classification with Natural Language Processing (Comparing BERT and Bi-Directional LSTM models for use with Twitter conversations)Master-uppsats, Lunds universitet/Matematisk statistik
Sammanfattning : We have constructed a novel neural network architecture called CWE-LSTM (concatenated word-emoji bidirectional long short-term memory) for classify- ing emotions in Twitter conversations. The architecture is based on a combina- tion of word and emoji embeddings with domain specificity in Twitter data. LÄS MER