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-
- 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)
-
- 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)
-
- 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:
- 11/03/2022
- 更改日期:
- 11/17/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
-
- 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:
- 11/03/2022
- 更改日期:
- 11/03/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Attribution License (ODC-By)
-
- 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:
- 11/02/2022
- 更改日期:
- 11/02/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)
-
- Type:
- Dataset
- 摘抄:
- Volume 53 (Fall 2022) of Cincinnati Romance Review. It includes ten articles and four book reviews.
- 作者:
- Sanz Casasnovas, Olga and Valladares-Ruiz, Patricia
- 提交者:
- Olga Sanz Casasnovas
- 上传日期:
- 10/03/2022
- 更改日期:
- 10/10/2022
- 创建:
- 2022
- 证书:
- Attribution 4.0 International
-
- Type:
- Dataset
- 摘抄:
- Volume 52 (Spring 2022). Special Issue on José Saramago. Guest Editor: Carlos Nogueira (Cátedra José Saramago–UTAD / Cátedra José Saramago–Universidade de Vigo)
- 作者:
- Valladares-Ruiz, Patricia and Sanz Casasnovas, Olga
- 提交者:
- Olga Sanz Casasnovas
- 上传日期:
- 10/03/2022
- 更改日期:
- 10/10/2022
- 创建:
- 2022
- 证书:
- Attribution 4.0 International
-
- Type:
- Dataset
- 摘抄:
- Data compiled and used for Guerra, Parlin & Matter
- 作者:
- Parlin, Adam; Guerra, Patrick, and Matter, Stephen F.
- 提交者:
- Stephen F. Matter
- 上传日期:
- 09/21/2022
- 更改日期:
- 09/21/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)
-
- Type:
- Image
- 摘抄:
- Box-and-Whisker visualization of coherence scores for three corpora types: Caselaw (cas), Pubmed Abstracts (pma), Pubmed Central (pmc). This figure is for models matching search-term "climate". Visualizations for other search terms and additional interactive elements available at the related URL below. 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]
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 08/12/2022
- 更改日期:
- 08/12/2022
- 创建:
- 2022
- 证书:
- Public Domain Mark 1.0
-
- Type:
- Image
- 摘抄:
- Box-and-Whisker visualization of topic coherence scores for three corpora types: Caselaw (cas), Pubmed Abstracts (pma), Pubmed Central (pmc). This figure is for models matching search-term "climate". Visualizations for other search terms and additional interactive elements available at related URL below. 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]
- 作者:
- McCabe, Erin E.
- 提交者:
- Erin E. McCabe
- 上传日期:
- 08/12/2022
- 更改日期:
- 08/12/2022
- 创建:
- 2022
- 证书:
- Open Data Commons Public Domain Dedication and License (PDDL)