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Part 1: Document Description
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Citation |
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Title: |
Textile Dataset for Applying into Machine Learning Models |
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Identification Number: |
doi:10.7910/DVN/HIZXSS |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2021-04-19 |
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Version: |
1 |
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Bibliographic Citation: |
Ngo, Vuong M., 2021, "Textile Dataset for Applying into Machine Learning Models", https://doi.org/10.7910/DVN/HIZXSS, Harvard Dataverse, V1 |
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Citation |
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Title: |
Textile Dataset for Applying into Machine Learning Models |
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Identification Number: |
doi:10.7910/DVN/HIZXSS |
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Authoring Entity: |
Ngo, Vuong M. (Trinity College Dublin) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Ngo, Vuong M. |
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Depositor: |
Ngo, Vuong M. |
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Date of Deposit: |
2021-04-19 |
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Study Scope |
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Keywords: |
Computer and Information Science, Textile structure, classification |
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Abstract: |
With the help of domain experts we created a data set containing a total of 1,600 fabrics divided into sixteen different categories, each containing 100 items of a particular type of textile. On average, each textile consists of 20,916 vertices, 5,229 hyperedges, 152 terminal nodes, 5,229 regular edges and 10,534 connected edges. The attached file is hypergraph representations which are extracted to k-neighbourhoods and then transferred to vector representations with normal frequence and TF-IDF. These vectors are applied into ML models. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Label: |
_sawutext_files.zip |
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Text: |
Hypegraph representation of textiles (aslo being SAWU text representation) designed by SAWU Editor in "Gyory. Generic Textile Structure Editor. IGI Global, 2014") |
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Notes: |
application/zip |