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  • Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions: Replication Package

    Generic Work thumbnail: Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions: Replication Package
    Type:
    Generic Work
    摘抄:
    Aurek Chattopadhyay, Reagan Maddox, Glen Horton, Nan Niu, Ganesh Malla, Tanmay Bhowmik, Jianzhang Zhang, and Juha Savolainen, Completeness of Natural Language Requirements: A Comparative Study of User Stories and Feature Descriptions (submitted to REFSQ 2023:  https://2023.refsq.org)
    作者:
    Chattopadhyay, Aurek and Niu, Nan
    提交者:
    Aurek Chattopadhyay
    上传日期:
    11/21/2022
    更改日期:
    11/21/2022
    证书:
    Open Data Commons Public Domain Dedication and License (PDDL)

  • Coherence_Evaluations - nvl_pollution.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_pollution.csv
    Type:
    Dataset
    摘抄:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) 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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_earth.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_earth.csv
    Type:
    Dataset
    摘抄:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) 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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_climate.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_climate.csv
    Type:
    Dataset
    摘抄:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) 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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_environmental.csv
    Type:
    Dataset
    摘抄:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) 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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • TV News Transcripts of Outer Space Coverage

    Dataset thumbnail: TV News Transcripts of Outer Space Coverage
    Type:
    Dataset
    摘抄:
    Text and Metadata for 14,399 newspaper articles. Transcripts collected from Internet Archive Date Range: 2010-2022 File includes meta/data: - Unique-id (uid) - Title (incl. search term) - Date - Link (url) - Abstract - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Newspaper coverage of Outer Space Theme

    Dataset thumbnail: Newspaper coverage of Outer Space Theme
    Type:
    Dataset
    摘抄:
    Text and Metadata for 9,061 newspaper articles. Newspapers included: New York Times, Wall Street Journal, & Washington Post Date Range: 2017-2022 File includes meta/data: - Unique-id (uid) - Title (incl. source paper & section name) - Date - Link (url) - Author - Text Text matching the following terms: - space explor* - space mission - space science - spaceship - space tour* - space transport* - spacecraft - space shuttle - outer space - astronom* - astrop* - astrona* - planet - NASA - star trek - star wars - lunar - space flight
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/12/2022
    更改日期:
    11/12/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - nvl_random5k.csv

    Dataset thumbnail: Coherence_Evaluations - nvl_random5k.csv
    Type:
    Dataset
    摘抄:
    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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/05/2022
    更改日期:
    11/11/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_environmental.csv

    Dataset thumbnail: Coherence_Evaluations - pmc_environmental.csv
    Type:
    Dataset
    摘抄:
    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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/04/2022
    更改日期:
    11/04/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)

  • Coherence_Evaluations - pmc_earth.csv

    Dataset thumbnail: Coherence_Evaluations - pmc_earth.csv
    Type:
    Dataset
    摘抄:
    CSV files containing the coherence scoring pertaining to datasets of: DocumentCount = 5,000 Corpus = (one from) Federal Caselaw [cas] / Pubmed-Abstracts [pma] / Pubmed-Central [pmc] / News [nws] SearchTerm[s] = (one from) 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
    作者:
    McCabe, Erin E.
    提交者:
    Erin E. McCabe
    上传日期:
    11/04/2022
    更改日期:
    11/04/2022
    创建:
    2022
    证书:
    Open Data Commons Attribution License (ODC-By)