Mining and analyzing digital archive usage data to support collection development decisions

We demonstrate a "collection development decision support tool" that mines digital archive usage data. We want to better understand the University of Southern California (USC) Digital Archive's collection structure by analyzing the objects' characteristics, by analyzing the relat...

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Hauptverfasser:	Ward, Jewel, Bollen, Johan, Pearson, Jeffrey, Chan, Shing-Cheung, Chi, Hui-Hsien, Chi, Marie, Guevara, Kristine, Huang, Hsiao-han, Kim, Genesan, Krivokon, Maks, Lee, Bo H., Li, Pei-Han, Muliawan, Fenny, Nguyen, Vu, Boehm, Barry W., Brown, A. Winsor, Colbert, Edward, Lam, Alex, Patel, Mayur
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithm design and analysis Applied computing > Computers in other domains > Digital libraries and archives Clustering algorithms co-retrieval collection development Data analysis Data mining Graphics Information systems > Information retrieval > Document representation > Document collection models Information systems > Information systems applications > Digital libraries and archives Software libraries usage analysis Visualization Web server
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Beschreibung
Zusammenfassung:	We demonstrate a "collection development decision support tool" that mines digital archive usage data. We want to better understand the University of Southern California (USC) Digital Archive's collection structure by analyzing the objects' characteristics, by analyzing the relationships between viewed objects, and by understanding usage trends over time. By relying on implicit patterns of usage data, such as co-retrievals, rather than explicit data, such as hit counts, we believe we can make more informed decisions about where to expend our resources.
DOI:	10.1145/1065385.1065521