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Journal of Machine Learning Research Corpus
Data Science and Analytics
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About
Contains detailed metadata for all papers published in the Journal of Machine Learning Research (JMLR). This resource enables advanced analysis of academic trends, bibliometrics, and research evolution within machine learning and artificial intelligence disciplines. Information for over 2,500 research articles was collected via scraping the official JMLR website, offering crucial insights into publication history, authorship, and content structure.
Columns
- title: The specific title of the published academic paper.
- volume: The volume number of the journal in which the paper was released.
- authors: A listing of the authors credited for the paper.
- year: The release year of the paper, spanning from 2000 to 2022.
- pages: The total number of pages in the publication (ranging from 2 to 124).
- link: A direct URL providing a link to the PDF version of the paper.
- code: A URL that links to any available supplementary code repository, although links are missing for approximately 90% of the records.
Distribution
The data is available in a standard file format, typically CSV, specifically referenced as
data.csv and is 605.06 kB in size. The dataset contains 2,894 valid records, each representing a unique paper entry. There are seven distinct columns of information included for each record.Usage
This dataset is suitable for academic research projects, bibliometric analysis, tracking long-term publication trends in AI, and developing models for citation analysis or academic natural language processing (NLP). It is also useful for researchers looking to identify high-impact authors or volumes within the machine learning domain.
Coverage
The dataset focuses on international academic publications within the Journal of Machine Learning Research (JMLR). The time range spans papers released between the years 2000 and 2022. There is full data availability across this period, with the majority of papers appearing in the later years (post-2017). The scope is specific to JMLR content; it does not cover publications from other journals.
License
CC0: Public Domain
Who Can Use It
- Academic Researchers: Analysing publication patterns and author networks.
- Data Scientists: Building predictive models based on paper characteristics or performing text analysis on titles and metadata.
- University Libraries/Archivists: Curating and indexing JMLR content history.
- Students: Gaining an overview of foundational and current machine learning literature.
Dataset Name Suggestions
- JMLR Academic Paper Metadata
- Journal of Machine Learning Research Corpus
- Machine Learning Publication History (2000-2022)
Attributes
Original Data Source: Journal of Machine Learning Research Corpus
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