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  • Coherence_Evaluations - cas_random5k.csv

    Dataset thumbnail: Coherence_Evaluations - cas_random5k.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    08/10/2022
    Fecha modificada:
    08/10/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - cas_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - cas_environmental.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    08/10/2022
    Fecha modificada:
    08/10/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - cas_pollution.csv

    Dataset thumbnail: Coherence_Evaluations - cas_pollution.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    08/10/2022
    Fecha modificada:
    08/10/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - cas_climate.csv

    Dataset thumbnail: Coherence_Evaluations - cas_climate.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / Chicago Novel Corpus [nvl] / Newspaper Corpus [nws] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    08/10/2022
    Fecha modificada:
    11/11/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - cas_earth.csv

    Dataset thumbnail: Coherence_Evaluations - cas_earth.csv
    Type:
    Dataset
    Descripción/Resumen:
    CSV files containing the topic coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one of) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] SearchTerm[s] = (one of) Earth / Environmental / Climate / Pollution / Random 5k documents of a specific corpus Coherence was scored across every combination of: TopicCount: 10-40 Hyperparameter-Alpha: [0.01, 0.31, 0.61, 0.91, symmetric, asymmetric] Hyperparameter-Beta: [0.01, 0.31, 0.61, 0.91, automatic, symmetric] The columns in this file include: Validation_Set: Which search term this scoring pertains to Topics: Number of topics in the model Alpha: Hyperparameter alpha selection from the 6 options above Beta: Hyperparameter beta selection from the 6 options above Coherence: The topic coherence score for the given model-row Perplexity: The perplexity score for the given model-row
    Creador/Autor:
    McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    08/10/2022
    Fecha modificada:
    08/10/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Samvera Presentation

    Generic Work thumbnail: Samvera Presentation
    Type:
    Generic Work
    Descripción/Resumen:
    This is a collection of items that I used in my Samvera History Presentation.
    Creador/Autor:
    Scherz, Thomas
    Peticionario:
    Thomas Scherz
    Fecha modificada:
    07/12/2022
    Fecha modificada:
    07/12/2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Poetry Foundation Metadata

    Dataset thumbnail: Poetry Foundation Metadata
    Type:
    Dataset
    Descripción/Resumen:
    This file contains poet metadata for a dataset of poems collected from Poetry Foundation. This metadata relates to a poetry corpus collected from Kaggle available on that site:  https://www.kaggle.com/datasets/ultrajack/modern-renaissance-poetry Sean Ayres collected publication metadata and generated other relevant metadata fields based on his subject matter expertise. The original Kaggle poetry dataset contains approximately X lines of poetry. The metadata for this dataset references X poets
    Creador/Autor:
    Ayres, Sean and McCabe, Erin E.
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    07/11/2022
    Fecha modificada:
    07/11/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Project Gutenberg Poetry Metadata

    Dataset thumbnail: Project Gutenberg Poetry Metadata
    Type:
    Dataset
    Descripción/Resumen:
    This file contains book metadata for a Project Gutenberg dataset of poetry metadata. This metadata relates to a poetry corpus collected by Allison Parrish available on GitHub:  https://github.com/aparrish/gutenberg-poetry-corpus Sean Ayres collected the publication metadata and generated other relevant metadata fields based on his subject matter expertise. The poetry dataset contains approximately three million lines of poetry The metadata for the dataset references X hundreds of books.
    Creador/Autor:
    Ayres, Sean; McCabe, Erin E., and Parrish, Allison
    Peticionario:
    Erin E. McCabe
    Fecha modificada:
    07/11/2022
    Fecha modificada:
    07/11/2022
    Fecha de creacion:
    2022
    Licencia:
    Open Data Commons Attribution License (ODC-By)

  • Iterations of the RDS Unit_2012-2022

    Document thumbnail: Iterations of the RDS Unit_2012-2022
    Type:
    Document
    Descripción/Resumen:
    This document is supplemental materials for the book chapter "Playing in the Same Sandbox: Collaborations on Data Management, Research Technologies, and Research Computing" in the book Cases on Establishing Effective Collaborations in Academic Libraries authored by Amy Koshoffer and Amy Latessa
    Creador/Autor:
    Koshoffer, Amy
    Peticionario:
    Amy Koshoffer
    Fecha modificada:
    04/18/2022
    Fecha modificada:
    04/18/2022
    Fecha de creacion:
    2022-04-18
    Licencia:
    Attribution-NonCommercial-ShareAlike 4.0 International

  • From In-person to Virtual Library Orientation: COVID-19 Pandemic’s Impact on Library Service to a China-United States Dual Degree Program

    Image thumbnail: From In-person to Virtual Library Orientation: COVID-19 Pandemic’s Impact on Library Service to a China-United States Dual Degree Program
    Type:
    Image
    Descripción/Resumen:
    University of Cincinnati (USA) and Chongqing University (China) established the first cooperation education based dual-degree undergraduate program in 2013 called Joint Co-op Institute. This strategic partnership involves librarians from both universities to work with students from orientation to graduation. Through collaborative efforts from multiple dimensions in academic and student affairs, librarians’ work is one of the key factors to the successful enrollment and retention rate. This poster highlights eight years of work between global services librarians from two institutions. It highlights the collaboration of two librarians conducting the first online orientation during the pandemic despite the challenges of technology, time difference and students’ anxiety.
    Creador/Autor:
    Zhang, Jie and Cheng, Hong
    Peticionario:
    Hong Cheng
    Fecha modificada:
    02/22/2022
    Fecha modificada:
    02/22/2022
    Fecha de creacion:
    2021-06-25
    Licencia:
    Attribution-NonCommercial-NoDerivs 4.0 International