Sökning: "Natural Language Processing NLP"
Visar resultat 21 - 25 av 229 uppsatser innehållade orden Natural Language Processing NLP.
21. SAX meets Word2vec : A new paradigm in the time series forecasting
Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologiSammanfattning : The purpose of this thesis was to investigate whether some successful ideas in NLP, such as word2vec, are applicable to time series prob- lems or not. More specifically, we are interested to assess a combina- tion of previously proven methods such as SAX and Word2vec. LÄS MER
22. Finding Quality Problems In Security Requirements Using NALABS
Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Security can be informally defined as the freedom from the conditions that cause a loss of assets. Security requirements are the ways that stakeholders, involved in a software engineering project, specify security in the end product. LÄS MER
23. Streamline searches in a database
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : The objective of this thesis is to explore technologies and solutions and see if it is possible to make a logistical flow more efficient. The logistical flow consists of a database containing materiel for purchase or reparation. As of now, searches may either result in too many results, of which several are irrelevant, or no results at all. LÄS MER
24. Sentiment Analysis for Swedish : The Impact of Emojis on Sentiment Analysis of Swedish Informal Texts
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : This study investigates the use of emojis in sentiment analysis for the Swedish language, with the objective to assess if emojis improve the performance of the model. Sentiment analysis is an NLP classification task aimed at extracting people's opinions, sentiments, and attitudes from language. LÄS MER
25. Using Social Media and Personality Predictions to Anticipate Startup Success
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : This thesis explores the potential of integrating predicted founder personalities, based on the Big 5 Personality Framework, into Machine Learning (ML) models to enhance the accuracy of early-stage startup success predictions. Leveraging Natural Language Processing (NLP) techniques, we extracted personality insights from founders' tweets, focusing on US startups funded between 2013 and 2015. LÄS MER