Important Entity Recognition in Web Page Text

The aim of this thesis is training named entity recognition model on a dataset created using structured data. Datasets were created from the names of products and books extracted from structured data in JSON-LD and Microdata format. Structured data were extracted from e-shop and social cataloging websites by web scraping. Names were used as a dataset by themselves as well as webpage text with automatically annotated matches of the names. In total eight models in Czech language were trained for recognizing names of products and books using spaCy library. F-score results are up to 89.94 for products and up to 84.26 for books evaluated on a created testing dataset