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Categorization based on Company Activities

Categorization based on Company Activities. Martin Repka , Ján Paralič Katedra kybernetiky a umelej inteligencie Fakulta elektrotechniky a informatiky Technická univerzita v Košiciach { Martin.Repka , Jan.Paralic }@ tuke.sk. Company Network.

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Categorization based on Company Activities

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  1. Categorization based on Company Activities Martin Repka, JánParalič Katedrakybernetiky a umelejinteligencie Fakultaelektrotechniky a informatiky Technickáuniverzita v Košiciach {Martin.Repka, Jan.Paralic}@tuke.sk

  2. Company Network • publicly accessed sources as Business Register of Slovak Republic (ORSR) • aggregated, analyzed and integrated within project ITLIS1 • featuring complete data model, which integrates structural, compositional and temporal (historical) data • aim • correlation between compositional data and online catalogue categories 1 www.itlis.eu

  3. Data • Amadeus - compositional data about 25683 companies • Azet - online catalogue entries in 15705 cases • Itlis - companies in 10 largest online cat. categories, • 2040 companies (ranging from 105 to 389 companies in category)

  4. Company categorization • classification of documents into categories • Text-mining technique • List of company activities as unstructured document

  5. Results • average accuracy • 10-fold cross-validation • average performance using mode values = 19.07% • RapidMiner

  6. Conclusions • data integration from several sources • experimentally verified correlation of compositional data (company activities) and online categorization • several model learners • time complexity and model accuracy • very efficient model learners seems to be SVM, Neural Network and Naive Bayes (Kernel) model • information could be useful as support to other analyses of company network.

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