CREAT: Census Research Exploration and Analysis Tool

LEHD Data Documentation LEHD-OVERVIEW-S2008-rev1

December 2011

Working Paper Number:

CES-11-43

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.
:
estimating, statistical, data census, report, census data, survey, respondent, linked census, yearly, longitudinal, metropolitan, population, housing, residential, census bureau, census file, aging, research census, censuses surveys, resident, census survey, prevalence

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.
:
Metropolitan Statistical Area, Annual Survey of Manufactures, Standard Statistical Establishment List, Internal Revenue Service, Standard Industrial Classification, Bureau of Labor Statistics, Social Security Administration, Service Annual Survey, Center for Economic Studies, Permanent Plant Number, Establishment Micro Properties, Current Population Survey, Longitudinal Business Database, Employer Identification Numbers, Survey of Income and Program Participation, Cornell University, Business Master File, Unemployment Insurance, Research Data Center, North American Industry Classification System, Social Security Number, Alfred P Sloan Foundation, Longitudinal Employer Household Dynamics, Business Register, Protected Identification Key, Employment History File, Employer Characteristics File, Individual Characteristics File, American Housing Survey, Quarterly Workforce Indicators, CDF, Core Based Statistical Area, Quarterly Census of Employment and Wages, Composite Person Record, Business Employment Dynamics, Local Employment Dynamics, Master Address File, Business Register Bridge, Disclosure Review Board, North American Industry Classi, Federal Tax Information

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.

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