Essays about: "Logganalys"

Showing result 1 - 5 of 7 essays containing the word Logganalys.

  1. 1. Predicting user churn using temporal information : Early detection of churning users with machine learning using log-level data from a MedTech application

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Love Marcus; [2023]
    Keywords : User churn; Customer attrition; Artificial neural networks; Log-level analysis; Random forests; Decision trees; Användarbortfall; Kundbortfall; Artificiella neurala nätverk; logganalys; Slumpskogar; Beslutsträd;

    Abstract : User retention is a critical aspect of any business or service. Churn is the continuous loss of active users. A low churn rate enables companies to focus more resources on providing better services in contrast to recruiting new users. READ MORE

  3. 2. How to Estimate Local Performance using Machine learning Engineering (HELP ME) : from log files to support guidance

    University essay from Linköpings universitet/Artificiell intelligens och integrerade datorsystem

    Author : Hugo Ekinge; [2023]
    Keywords : Machine learning; GRU; 1D-CNN; Transformer; log analysis; parameter estimation; regression; performance monitoring; deep learning; troubleshooting; support; Maskininlärning; GRU; 1D-CNN; Transformer; logganalys; parameteruppskattning; regression; prestandaövervakning; djupinlärning; felsökning; support;

    Abstract : As modern systems are becoming increasingly complex, they are also becoming more and more cumbersome to diagnose and fix when things go wrong. One domain where it is very important for machinery and equipment to stay functional is in the world of medical IT, where technology is used to improve healthcare for people all over the world. READ MORE

  4. 3. Integrating Telecommunications-Specific Language Models into a Trouble Report Retrieval Approach

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Nathan Bosch; [2022]
    Keywords : information retrieval; neural ranking; trouble reports; log analysis; natural language processing; informationssökning; neural rangordning; felrapporter; logganalys; naturlig språkbehandling;

    Abstract : In the development of large telecommunications systems, it is imperative to identify, report, analyze and, thereafter, resolve both software and hardware faults. This resolution process often relies on written trouble reports (TRs), that contain information about the observed fault and, after analysis, information about why the fault occurred and the decision to resolve the fault. READ MORE

  5. 4. Discover patterns within train log data using unsupervised learning and network analysis

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Zehua Guo; [2022]
    Keywords : Log analysis; Natural language processing; Unsupervised learning; Clustering; Network analysis; Logganalys; Bearbetning av naturligt språk; Oövervakat lärande; Clustering; Nätverksanalys;

    Abstract : With the development of information technology in recent years, log analysis has gradually become a hot research topic. However, manual log analysis requires specialized knowledge and is a time-consuming task. Therefore, more and more researchers are searching for ways to automate log analysis. READ MORE

  6. 5. Classifying and Comparing Latent Space Representation of Unstructured Log Data.

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Bharat Sharma; [2021]
    Keywords : Machine learning; Natural language processing; Deep learning; Classification; Supervised learning; Transformer models; Sentence embeddings; Doc2Vec; Deep averaging networks.; Maskininlärning; naturligtspråkbehandling; djupinlärning; klassificering; övervakad inlärning; transformeringsmodeller; meningsinbäddningar; Doc2Vec; djupa linjärkombinerande nätverk.;

    Abstract : This thesis explores and compares various methods for producing vector representation of unstructured log data. Ericsson wanted to investigate machine learning methods to analyze logs produced by their systems to reduce the cost and effort required for manual log analysis. READ MORE