Abstract: Techniques for determining a new industry classification for a company are described. An industry classifier can access company data of a company and profile data of an employee of the company. Additionally, a plurality of updated classifications associated with the company can be accessed from an industry taxonomy database. A featurization process can calculate a classification score for each updated classification based on the accessed data. Additionally, the featurization process can determine a new industry classification for the company based on the calculation. Subsequently, a company page updater can update a company page associated with the company by adding the new industry classification to the company page.

Abstract: In an example embodiment, a solution that automatically predicts an industry for a candidate company is provided. An existing industry classifier is trained using a first machine learning algorithm, the first machine learning algorithm taking as input first training data and existing industries listed in an industry taxonomy. A new industry classifier is trained using a second machine learning algorithm, the second machine learning algorithm taking as input second training data and new industries listed in an industry taxonomy. Then the candidate company is fed into the existing industry classifier, producing one or more predicted existing industries corresponding to the candidate company. The candidate company is also fed into the new industry classifier, producing one or more predicted new industries corresponding to the candidate company. One or more final predicted industries are selected from among the one or more predicted existing industries and the one or more predicted new industries.

Abstract: In an example embodiment, a solution that automatically predicts an industry for a candidate company is provided. An existing industry classifier is trained using a first machine learning algorithm, the first machine learning algorithm taking as input first training data and existing industries listed in an industry taxonomy. A new industry classifier is trained using a second machine learning algorithm, the second machine learning algorithm taking as input second training data and new industries listed in an industry taxonomy. Then the candidate company is fed into the existing industry classifier, producing one or more predicted existing industries corresponding to the candidate company. The candidate company is also fed into the new industry classifier, producing one or more predicted new industries corresponding to the candidate company. One or more final predicted industries are selected from among the one or more predicted existing industries and the one or more predicted new industries.

Abstract: Techniques for determining a new industry classification for a company are described. An industry classifier can access company data of a company and profile data of an employee of the company. Additionally, a plurality of updated classifications associated with the company can be accessed from an industry taxonomy database. A featurization process can calculate a classification score for each updated classification based on the accessed data. Additionally, the featurization process can determine a new industry classification for the company based on the calculation. Subsequently, a company page updater can update a company page associated with the company by adding the new industry classification to the company page.