Sökning: "Word embeddings"
Visar resultat 1 - 5 av 91 uppsatser innehållade orden Word embeddings.
1. Towards Automated Log Message Embeddings for Anomaly Detection
Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknikSammanfattning : Log messages are implemented by developers to record important runtime information about a system. For that reason, system logs can provide insight into the state and health of a system and potentially be used to anticipate and discover errors. LÄS MER
2. Detection of insurance fraud using NLP and ML
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : Machine-Learning can sometimes see things we as humans can not. In this thesis we evaluated three different Natural Language Procces-techniques: BERT, word2vec and linguistic analysis (UDPipe), on their performance in detecting insurance fraud based on transcribed audio from phone calls (referred to as audio data) and written text (referred to as text-form data), related to insurance claims. LÄS MER
3. Image-Guided Zero-Shot Object Detection in Video Games : Using Images as Prompts for Detection of Unseen 2D Icons
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Object detection deals with localization and classification of objects in images, where the task is to propose bounding boxes and predict their respective classes. Challenges in object detection include large-scale annotated datasets and re-training of models for specific tasks. LÄS MER
4. Classifying personal data on contextual information
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. LÄS MER
5. Cross-Lingual and Genre-Supervised Parsing and Tagging for Low-Resource Spoken Data
Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologiSammanfattning : Dealing with low-resource languages is a challenging task, because of the absence of sufficient data to train machine-learning models to make predictions on these languages. One way to deal with this problem is to use data from higher-resource languages, which enables the transfer of learning from these languages to the low-resource target ones. LÄS MER