Sökning: "machine learning text analysis"

Visar resultat 11 - 15 av 131 uppsatser innehållade orden machine learning text analysis.

1. 11. Streamline searches in a database

   Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :David Ellerblad Valtonen; André Franzén; [2023]
   Nyckelord :AI; NLP; ML; Artificial Intelligence; Natural Language Processing; Machine Learning; text-to-sql; seq-to-seq; sequence-to-sequence;

   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

3. 12. Contextual short-term memory for LLM-based chatbot

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

   Författare :Mikael Lauri Aleksi Törnwall; [2023]
   Nyckelord :Chatbot; Artificial Intelligence; Machine Learning; Language Model; Large Language Model; GPT-3; Natural Language Processing; Text Summarization; Dialogue Summarization; Prompt Design; Prompt Programming; Chatbot; Artificiell Intelligens; Maskininlärning; Språkmodell; Stor Språkmodell; GPT-3; Naturlig Ppråkbehandling; Textsammanfattning; Sammanfattning av Dialog; Design för Inmatningsprompt; Inmatningsprompt Programmering;

   Sammanfattning : The evolution of Language Models (LMs) has enabled building chatbot systems that are capable of human-like dialogues without the need for fine-tuning the chatbot for a specific task. LMs are stateless, which means that a LM-based chatbot does not have a recollection of the past conversation unless it is explicitly included in the input prompt. LÄS MER

4. 13. The Influence of Artificial Intelligence on Songwriting : Navigating Attribution Challenges and Copyright Protection

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

   Författare :Karin Norberg; Othilia Norell; [2023]
   Nyckelord :Artificial Intelligence; Attribution; Copyright; Machine Learning; Music; Natural Language Processing; Royalties; Songwriting;

   Sammanfattning : This report explores the evolving landscape of songwriting and copyright protection, with a focus on the influence of Artificial Intelligence (AI). It highlights the need for objective measures of attribution in music co-creation, including collaborations involving AI. LÄS MER

5. 14. Biases in AI: An Experiment : Algorithmic Fairness in the World of Hateful Language Detection

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

   Författare :Anna Stozek; [2023]
   Nyckelord :machine learning; algorithmic fairness; unintended bias; sentiment analysis; automated hate detection; maskininlärning; algoritmisk rättvisa; oavsiktlig bias; sentimentanalys; automatisk hatdetektion;

   Sammanfattning : Hateful language is a growing problem in digital spaces. Human moderators are not enough to eliminate the problem. Automated hateful language detection systems are used to aid the human moderators. One of the issues with the systems is that their performance can differ depending on who is the target of a hateful text. LÄS MER

7. 15. Prisestimering på bostadsrätter : Implementering av OCR-metoder och Random Forest regression för datadriven värdering

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

   Författare :Sofia Lövgren; Marcus Löthman; [2023]
   Nyckelord :OCR; Optical Character recognition; Random Forest regression; price estimation; housing cooperatives; machine learning; OCR; Optisk teckenigenkänning; Random Forest regression; Prisestimering; Bostadsrätter; Maskininlärning;

   Sammanfattning : This thesis explores the implementation of Optical Character Recognition (OCR) – based text extraction and random forest regression analysis for housing market valuation, specifically focusing on the impact of value factors, derived from OCR-extracted economic values from housing cooperatives’ annual reports. The objective is to perform price estimations using the Random Forest model to identify the key value factors that influence the estimation process and examine how the economic values from annual reports affect the sales price. LÄS MER