CREAT: Census Research Exploration and Analysis Tool

NBER Patent Data-BR Bridge: User Guide and Technical Documentation

October 2010

Working Paper Number:

CES-10-36

Abstract

This note provides details about the construction of the NBER Patent Data-BR concordance, and is intended for researchers planning to use this concordance. In addition to describing the matching process used to construct the concordance, this note provides a discussion of the benefits and limitations of this concordance.

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.
:
researcher, enterprise, manufacturing, technological, growth, technology, invention, research, incorporated, innovation, inventory, patent, patenting, productivity plants, trademark, innovative, firms patents, corp

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.
:
National Science Foundation, Metropolitan Statistical Area, Service Annual Survey, National Bureau of Economic Research, Employer Identification Number, IBM, Longitudinal Business Database, University of California Los Angeles, Census of Manufacturing Firms, Economic Census, Research Data Center, Patent and Trademark Office, Business Register, Integrated Longitudinal Business Database

Similar Working Papers Similarity between working papers are determined by an unsupervised neural network model know as Doc2Vec.

Doc2Vec is a model that represents entire documents as fixed-length vectors, allowing for the capture of semantic meaning in a way that relates to the context of words within the document. The model learns to 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 document vectors are compared using cosine similarity/distance to determine the most similar working papers. Papers identified with 🔥 are in the top 20% of similarity.

The 10 most similar working papers to the working paper 'NBER Patent Data-BR Bridge: User Guide and Technical Documentation' are listed below in order of similarity.