Patterns of information – clustering books and readers in open access libraries

DOI

The question is how open access libraries can offer comparable services to online retailers such as Amazon.com while retaining the readers’ privacy. A possible solution can be found in analysing the preferences of groups or communities. In other words, to explore the possibility to uncover sets of documents with a meaningful connection for groups of readers. The solution depends on examining patterns of usage, instead of storing information about readers.This paper will investigate the possibility to uncover the preferences of user groups within an open access digital library using social networking analysis techniques

Date: 2012

Date: 2014

The depositor of the data provided data in the xls format, DANS converted this into csv and pdf for durability reasons and placed the converted files in the folder 'Csv and pdf conversions'.

Identifier
DOI https://doi.org/10.17026/dans-x72-d9h2
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-x72-d9h2
Provenance
Creator R. Snijder
Publisher DANS Data Station Phys-Tech Sciences
Contributor R. Snijder
Publication Year 2017
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact R. Snijder (OAPEN Foundation)
Representation
Resource Type Dataset
Format application/pdf; text/csv; application/vnd.openxmlformats-officedocument.spreadsheetml.sheet; application/zip
Size 2449739; 11146; 16077; 6072; 26078; 40098; 189465; 103643; 98149; 229533; 1031; 2087; 353; 122163; 210; 338; 195; 461715; 131360; 709848; 387103; 187865; 632532; 714; 196; 245513; 342; 758469; 154417; 157379; 3845472; 14000; 8123; 196555; 8211; 3702; 923873; 6443104; 4972544; 10855; 4540; 346600; 8309; 889851; 8130472; 1487274
Version 2.0
Discipline Other