White Papers

Useful white papers from KNIME.

IoT

Anomaly Detection

Anomaly Detection I: Time Alignment and Visualization for Anomaly Detection (2015)

Here we show how we prepared and visualized FFT-transformed sensor data from a rotor equipment: frequency binning, time alignment, and visualization.

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  • Workflow "Time Alignment and Visualization" is available on the KNIME EXAMPLES server under 050_Applications/050017_AnomalyDetection/Pre-processing
  • 050_Applications/050017_AnomalyDetection/data also contains a reduced version of the original data set
  • Download full data set

Anomaly Detection II: Anomaly Detection in Predictive Maintenance (2015)

This second whitepaper of the anomaly detection series approaches the prediction of the “unknown” and possibly catastrophic event from a time series perspective. Chart Control and Auto-Regressive models are used to trigger alarms when the underlying system starts wandering off the known working condition.

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  • Workflow and data can be found on the KNIME EXAMPLES server under 050_Applications/050017_AnomalyDetection/Time Series Analysis

Energy

KNIME opens the Doors to Big Data. A practical Example of integrating any Big Data Platform into KNIME (2015)

In this whitepaper we show step-by-step how to integrate a big data platform into a KNIME workflow, using dedicated and/or generic connector nodes to connect to big data platforms and SQL helper nodes. Example workflow can be found on the EXAMPLES server under 004_Database/004005_Energy_Prepare_Data (Big Data).

Big data, Smart Energy, and Predictive Analytics (2013)

This whitepaper focuses on smart energy data from the Irish Smart Energy Trials. The first goal is to identify a few groups with common electricity behavior to create customized contract offers. The second goal is a reliable prediction of the overall energy consumption using time series prediction techniques.

Cities

Taming the Internet of Things with KNIME: Data Enrichment, Visualization, Time Series Analysis, and Optimization (2014)

This paper describes a number of techniques for data enrichment through responses from external RESTful services-analytics, model optimization, and visualization - from R graphic libraries to geo-localization with Open Street Maps and network visualization.

Social Media

Analyzing the Web from Start to Finish: Knowledge Extraction from a Web Forum using KNIME (2013)

This whitepaper covers all steps to extract knowledge from a web forum:crawls the forum and downloads the data, calculates some simple statistics, detects the discussed topics, and shows the experts for each topic.

Usable Customer Intelligence from Social Media Data: Clustering the Social Community (2012)

This whitepaper takes the next step beyond text mining and network analytics to perform clustering on the newly created insight.

Usable Customer Intelligence from Social Media Data: Network Analytics meets Text Mining (2012)

Text mining and network analytics are combined here to better position negative and positive users in context with their weight as influencers or followers inside the discussion forum.

Social Media, Recommandation Engines and Real-Time Model Execution with KNIME and ADAPA (2011)

This whitepaper shows an example of how advanced analytics combined with real-time execution can provide an end to end solution from model development to operational deployment and real time execution within any business process.

Web Analytics

Geolocalization of KNIME Downloads as a static Report and as a Movie (2014)

This whitepaper extracts IP addresses from a web log file and transforms them to points on a world map, producing a report with images and movie of the daily IP addresses. Example workflows are available on the EXAMPLES Server under 008_WebAnalytics_and_OpenStreetMap.

ETL - Pre-Processing

Seven Techniques for Data Dimensionality Reduction (2015)

Exploring and comparing seven different dimensionality reduction techniques: Missing Values, Low Variance Filter, High Correlation Filter, PCA, Random Forests, Backward feature Elimination, Forward feature Construction.

The KNIME Text Processing Feature: An Introduction (2012)

This technical report explains the fundamentals of text processing feature in KNIME along with detailed descriptions and examples of all key node categories.