Pirate's Treasure
January 2017
Working Paper Number:
CES-17-51
Abstract
Document Tags and Keywords
Keywords
Keywords are automatically generated using KeyBERT, a powerful and innovative
keyword extraction tool that utilizes BERT embeddings to ensure high-quality and contextually relevant
keywords.
By analyzing the content of working papers, KeyBERT identifies terms and phrases that capture the essence of the
text, highlighting the most significant topics and trends. This approach not only enhances searchability but
provides connections that go beyond potentially domain-specific author-defined keywords.
:
manufacturing,
industrial,
company,
invention,
import,
export,
manufacturer,
product,
subsidiary,
exporting,
exporter,
innovation,
multinational,
inventory,
patent,
innovate,
country,
patenting,
industrialized,
gdp,
firms export,
exported,
innovative,
firms patents,
patented,
patents firms
Tags
Tags are automatically generated using a pretrained language model from spaCy, which excels at
several tasks, including entity tagging.
The model is able to label words and phrases by part-of-speech,
including "organizations." By filtering for frequent words and phrases labeled as "organizations", papers are
identified to contain references to specific institutions, datasets, and other organizations.
:
Census of Manufactures,
Annual Survey of Manufactures,
Standard Industrial Classification,
Federal Reserve Bank,
Longitudinal Business Database,
Department of Economics,
North American Free Trade Agreement,
World Bank,
Census of Manufacturing Firms,
Patent and Trademark Office,
Longitudinal Firm Trade Transactions Database,
Customs and Border Protection
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associate a unique vector with each document while simultaneously learning word vectors, enabling tasks such as
document classification, clustering, and similarity detection by preserving the order and structure of words. The
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