Sökning: "Graph Embedding"

Visar resultat 1 - 5 av 32 uppsatser innehållade orden Graph Embedding.

  1. 1. Constructing and representing a knowledge graph(KG) for Positive Energy Districts (PEDs)

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Mahtab Davari; [2023]
    Nyckelord :Knowledge graph; Positive Energy Districts PEDs ; longest path; Questions and Answers; Community Detection; Node Embedding; t-SNE plots; Edge Prediction;

    Sammanfattning : In recent years, knowledge graphs(KGs) have become essential tools for visualizing concepts and retrieving contextual information. However, constructing KGs for new and specialized domains like Positive Energy Districts (PEDs) presents unique challenges, particularly when dealing with unstructured texts and ambiguous concepts from academic articles. LÄS MER

  3. 2. Sustainable Recipe Recommendation System: Evaluating the Performance of GPT Embeddings versus state-of-the-art systems

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Jaya Shankar Bandaru; Sai Keerthi Appili; [2023]
    Nyckelord :Sustainable Recipe Recommendation; Recommendation System; GPT-embeddings; PinSage; Factorization Machines;

    Sammanfattning : Background: The demand for a sustainable lifestyle is increasing due to the need to tackle rapid climate change. One-third of carbon emissions come from the food industry; reducing emissions from this industry is crucial when fighting climate change. LÄS MER

  4. 3. RNN-based Graph Neural Network for Credit Load Application leveraging Rejected Customer Cases

    Uppsats för yrkesexamina på avancerad nivå, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Oskar Nilsson; Benjamin Lilje; [2023]
    Nyckelord :Machine Learning; Deep Learning; Reject Inference; GNN; GCN; Graph Neural Networks; RNN; Recursive Neural Network; LSTM; Semi-Supervised Learning; Encoding; Decoding; Feature Elimination;

    Sammanfattning : Machine learning plays a vital role in preventing financial losses within the banking industry, and still, a lot of state of the art and industry-standard approaches within the field neglect rejected customer information and the potential information that they hold to detect similar risk behavior.This thesis explores the possibility of including this information during training and utilizing transactional history through an LSTM to improve the detection of defaults. LÄS MER

  5. 4. Imitation Learning on Branching Strategies for Branch and Bound Problems

    Master-uppsats, KTH/Matematisk statistik

    Författare :Magnus Axén; [2023]
    Nyckelord :Graph Networks; Convolutions; MIP; Branch and Bound; Facility Location Problem; MDP; Imitation Learning; Graf nätverk; Faltning; Blandade heltaltsproblem; Branch and Bound; Facility Location Problem; Markov; Imitationsinlärning;

    Sammanfattning : A new branch of machine and deep learning models has evolved in constrained optimization, specifically in mixed integer programming problems (MIP). These models draw inspiration from earlier solver methods, primarily the heuristic, branch and bound. LÄS MER

  7. 5. On the use of knowledge graph embeddings for business expansion

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

    Författare :Niklas Rydberg; [2022]
    Nyckelord :Knowledge Graph Embeddings; Knowledge Graphs; Link Prediction; Machine Learning; Artificial Intelligence; Kunskapsgrafinbäddningar; Kunskapsgrafer; Länkförutsägelser; Maskininlärning; Artificiell Intelligens;

    Sammanfattning : The area of Knowledge Graphs has grown significantly during recent time and has found many different applications both in industrial and academic settings. Despite this, many large Knowledge Graphs are in fact incomplete, which leads to the problem of finding the missing facts in the graphs using Link Prediction. LÄS MER