Avancerad sökning
Visar resultat 1 - 5 av 502 uppsatser som matchar ovanstående sökkriterier.
1. An In-Depth study on the Utilization of Large Language Models for Test Case Generation
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : This study investigates the utilization of Large Language Models for Test Case Generation. The study uses the Large Language model and Embedding model provided by Llama, specifically Llama2 of size 7B, to generate test cases given a defined input. LÄS MER
2. Collaborative Learning in an Immersive Virtual Environment: The Effects of Context and Retrieval Practice
Master-uppsats, Lunds universitet/Institutionen för psykologiSammanfattning : The accessibility of Virtual Reality (VR) enables the investigation of desirable difficulties originating from memory research with increased ecological validity. The two desirable difficulties include contextual variation and retrieval practice. LÄS MER
3. NLP i sökmotorer : Informationssökning och språkteknologi
Kandidat-uppsats, Karlstads universitet/Handelshögskolan (from 2013)Sammanfattning : Sökmotorer har blivit en allt viktigare del i människors informationshantering för att uppfylla olika behov. I en pressad situation ställs detta på sin spets, antingen det rör sig om en akut kris eller bara den moderna människans tidspress. I en sådan situation är det viktigt att enkelt kunna hitta rättinformation. LÄS MER
4. Designing for Learning in Enterprise Software - An explorative case study investigating admin user needs for learning, instruction, and information retrieval.
Master-uppsats, Göteborgs universitet/Graduate SchoolSammanfattning : Enterprise software plays a vital role in an organization's path to operational excellence and competitiveness. Whether or not the company is able to reap the rewards of the enterprise software depends largely on the extent to which the software is adopted effectively, meaning used with a high level of proficiency by its users. LÄS MER
5. Generating an Interpretable Ranking Model: Exploring the Power of Local Model-Agnostic Interpretability for Ranking Analysis
Magister-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : Machine learning has revolutionized recommendation systems by employing ranking models for personalized item suggestions. However, the complexity of learning-to-rank (LTR) models poses challenges in understanding the underlying reasons contributing to the ranking outcomes. LÄS MER