Illinois Data Bank - Dataset

Frequent pattern subject transactions from the University of Illinois Library (2016 - 2018)
Cite this dataset:
Hahn, Jim (2019): Frequent pattern subject transactions from the University of Illinois Library (2016 - 2018). University of Illinois at Urbana-Champaign. https://doi.org/10.13012/B2IDB-9440404_V1
Dataset Description

The data are provided to illustrate methods in evaluating systematic transactional data reuse in machine learning. A library account-based recommender system was developed using machine learning processing over transactional data of 383,828 transactions (or check-outs) sourced from a large multi-unit research library. The machine learning process utilized the FP-growth algorithm over the subject metadata associated with physical items that were checked-out together in the library. The purpose of this research is to evaluate the results of systematic transactional data reuse in machine learning. The analysis herein contains a large-scale network visualization of 180,441 subject association rules and corresponding node metrics.
Subject Social Sciences
Keywords evaluating machine learning; network science; FP-growth; WEKA; Gephi; personalization; recommender systems
License CC0
Funder Research and Publications Committee of the University of Illinois Library -Grant:81034
Corresponding Creator Jim Hahn
Downloaded 672 times
Version DOI Comment Publication Date
1 10.13012/B2IDB-9440404_V1 2019-05-31

Open in Globus File Manager what's this?
13.3 KB File
3.67 MB File
11 MB File
104 KB File
3.5 MB File

Contact the Research Data Service for help interpreting this log.

RelatedMaterial update: {"uri"=>[nil, "hdl.handle.net/2142/105401"], "uri_type"=>[nil, "Handle"], "datacite_list"=>[nil, "IsSupplementTo"], "note"=>[nil, ""], "feature"=>[nil, false]} 2024-02-05T21:15:25Z
RelatedMaterial update: {"uri"=>["", "hdl.handle.net/2142/103843"], "uri_type"=>["", "Handle"], "datacite_list"=>["", "IsSupplementTo"], "note"=>[nil, ""], "feature"=>[nil, false]} 2024-02-05T21:15:25Z
RelatedMaterial create: {"material_type"=>"Article", "availability"=>nil, "link"=>"http://hdl.handle.net/2142/105401", "uri"=>nil, "uri_type"=>nil, "citation"=>"Jim Hahn. 2019. Evaluating systematic transactional data enrichment and reuse. In Artificial Intelligence for Data Discovery and Reuse 2019 (AIDR '19), May 13–15, 2019, Pittsburgh, PA, USA. ACM, New York, NY, USA. https://doi.org/10.1145/3359115.3359116", "dataset_id"=>955, "selected_type"=>"Article", "datacite_list"=>nil} 2019-08-27T16:54:44Z
RelatedMaterial update: {"uri"=>[nil, ""], "uri_type"=>[nil, ""], "datacite_list"=>[nil, ""]} 2019-05-31T20:20:44Z
Dataset update: {"version_comment"=>[nil, ""], "subject"=>[nil, "Social Sciences"]} 2019-05-31T20:20:44Z