Trinity College Dublin, Department of Computer Science
Hayes, Conor; Cunningham, Pádraig; Smyth, Barry. 'A Case-Based Reasoning View of Automated Collaborative Filtering'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2001-09, 2001, pp15
Computer Science Technical Report TCD-CS-2001-09
From some perspectives Automated Collaborative Filtering (ACF)
appears quite similar to Case-Based Reasoning (CBR). It works on data
organised around users and assets that might be considered case descriptions. In
addition, in some versions of ACF, much of the induction is deferred to run
time – in the lazy learning spirit of CBR. On the other hand, because of its lack
of semantic descriptions it seems to be the antithesis of case-based reasoning –
a learning approach based on case representations. This paper analyses the
characteristics shared by ACF and CBR, it highlights the differences between
the two approaches and attempts to answer the question “When is it useful or
valid to consider ACF as CBR?”. We argue that a CBR perspective on ACF can
only be useful if it offers insights into the ACF process and supports a transfer
of techniques. In conclusion we present a case retrieval net model of ACF and
show how it allows for enhancements to the basic ACF idea.
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