Sökning: "sentence embeddings"

Visar resultat 11 - 15 av 37 uppsatser innehållade orden sentence embeddings.

1. 11. Sentence Embeddings and Automatic Classification of Menu Items

   Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Aljaz Kovac; [2022]
   Nyckelord :;

   Sammanfattning : Caspeco AB is a company in Uppsala that specializes in providing IT solutions to the hospitality industry. Their customers (restaurants, pubs, etc.) classify their menu items freely, which leads to a classification that is often inconsistent and unreliable. LÄS MER

3. 12. Methods for increasing cohesion in automatically extracted summaries of Swedish news articles : Using and extending multilingual sentence transformers in the data-processing stage of training BERT models for extractive text summarization

   Kandidat-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Elsa Andersson; [2022]
   Nyckelord :NLP; automatic text summarization; extractive summarization; BERT; sentence embeddings; cohesion;

   Sammanfattning : Developments in deep learning and machine learning overall has created a plethora of opportunities for easier training of automatic text summarization (ATS) models for producing summaries with higher quality. ATS can be split into extractive and abstractive tasks; extractive models extract sentences from the original text to create summaries. LÄS MER

4. 13. Automated Trouble Report Labeling : In The Telecom Industry

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Bergkvist Alexander; [2022]
   Nyckelord :Support Ticket labeling;

   Sammanfattning : Trouble reporting is a substantial component in any technical product's maintenance workflow. In this project, we investigated a set of methods for streamlining this workflow, using both software solutions and machine learning. The aim was to find a way of grouping trouble reports for easier analysis and other potential usecases down the line. LÄS MER

5. 14. Optimizing the Performance of Text Classification Models by Improving the Isotropy of the Embeddings using a Joint Loss Function

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

   Författare :Joseph Attieh; [2022]
   Nyckelord :Text Classification; Isotropy; Embeddings; BERT; IsoScore; Klassificering av Text; Isotropi; Inbäddningar; BERT; IsoScore;

   Sammanfattning : Recent studies show that the spatial distribution of the sentence representations generated from pre-trained language models is highly anisotropic, meaning that the representations are not uniformly distributed among the directions of the embedding space. Thus, the expressiveness of the embedding space is limited, as the embeddings are less distinguishable and less diverse. LÄS MER

7. 15. Improving BERTScore for Machine Translation Evaluation Through Contrastive Learning

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Oreen Yousuf; [2022]
   Nyckelord :machine translation; evaluation; BERTScore; contrastive learning; SimCSE; Hausa; Somali; Chinese;

   Sammanfattning : Since the advent of automatic evaluation, tasks within Natural Language Processing (NLP), including Machine Translation, have been able to better utilize both time and labor resources. Later, multilingual pre-trained models (MLMs)have uplifted many languages’ capacity to participate in NLP research. LÄS MER