Sökning: "Customer Classification"

Visar resultat 1 - 5 av 155 uppsatser innehållade orden Customer Classification.

1. 1. Effectivisation of keywords extraction process : A supervised binary classification approach of scraped words from company websites

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Josef Andersson; Max Fremling; [2023]
   Nyckelord :Machine learning; keyword classification; unbalanced data; word embedding;

   Sammanfattning : In today’s digital era, establishing an online presence and maintaining a well-structured website is vitalfor companies to remain competitive in their respective markets. A crucial aspect of online success liesin strategically selecting the right words to optimize customer engagement and search engine visibility. LÄS MER

3. 2. Prompt-learning and Zero-shot Text Classification with Domain-specific Textual Data

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

   Författare :Hengyu Luo; [2023]
   Nyckelord :prompt-learning; zero-shot; few-shot; text classification; domain-specific; retail sector domain; customer-agent interaction; transformer; large language models; ChatGPT; natural language processing; machine learning; deep learning;

   Sammanfattning : The rapid growth of textual data in the digital age presents unique challenges in domain-specific text classification, particularly the scarcity of labeled data for many applications, due to expensive cost of manual labeling work. In this thesis, we explore the applicability of prompt-learning method, which is well-known for being suitable in few-shot scenarios and much less data-consuming, as an emerging alternative to traditional fine-tuning methods, for domain-specific text classification in the context of customer-agent interactions in the retail sector. LÄS MER

4. 3. Multi-Class Classification for Predicting Customer Satisfaction : Application of machine learning methods to predict customer satisfaction at IKEA

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Stina Backerholm; Malin Börjesjö; [2023]
   Nyckelord :Multi-Class Classification; Imbalanced Data; Machine Learning; Multi-Klass Klassifisering; Obalanserat Data; Maskininlärning;

   Sammanfattning : Gaining a comprehensive understanding of the features that contribute to customer satisfaction after contact with IKEA’s Remote Customer Meeting Points (RCMPs) is essential for implementing effective remedial measures in the future. The aim of this project is to investigate if it is possible to find key features that influence customer satisfaction and to use these to predict customer satisfaction. LÄS MER

5. 4. AI-POWERED TEXT ANALYSIS TOOL FOR SENTIMENT ANALYSIS

   Kandidat-uppsats, Mälardalens universitet/Akademin för innovation, design och teknik

   Författare :Dani Kebede; Naod Tesfai; [2023]
   Nyckelord :Sentiment analysis; Artificial intelligence; NLP; RoBERTa;

   Sammanfattning : In today’s digital era, text data plays a ubiquitous role across various domains. This bachelor thesis focuses on the field of sentiment analysis, specifically addressing the task of classifying text into positive, negative, or neutral sentiments with the help of an AI tool. LÄS MER

7. 5. Predicting Short-term Absences of a Railway Crew using Historical Data

   Master-uppsats, KTH/Matematisk statistik

   Författare :Agnes Björnfot; Sandra Fjelkestam; [2023]
   Nyckelord :statistics; machine learning; absence prediction; random forest; XGBoost; quantile regression; statistik; maskininlärning; frånvaroprognoser; random forest; XGBoost; kvantilregression;

   Sammanfattning : Transportation via train is considered the most environmentally friendly way of traveling and is widely seen as the future of transportation. Canceled and delayed trains worsen customer satisfaction; thus, punctual trains are crucial for railway companies. LÄS MER