Chardonnens, Anne

Hengchen, Simon

English

The recent development of Web Analytics offers new perspectives to libraries, archives and museums to improve their knowledge of user needs and behaviours. In order to dive into the mind of their end users, institutions canexplore queries from a digital catalogue. However, a manual exploration demandsa major time commitment and only leads to limited results. This paperexplores how text mining techniques can help automate the analysis of largevolumes of log files. A 5-step methodology including clustering is illustratedby a case study from the State Archives of Belgium.info:eu-repo/semantics/publishe

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Text Mining for User Query Analysis: A 5-Step Method for Cultural Heritage Institutions

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https://helda.helsinki.fi/bitstream/10138/310185/1/ISI_17_ONLINE_FINAL.pdf

Text Mining for User Query Analysis: A 5-Step Method for Cultural Heritage Institutions

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Helsingin yliopiston digitaalinen arkisto