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Titlebook: Case-Based Reasoning Research and Development; 4th International Co David W. Aha,Ian Watson Conference proceedings 2001 Springer-Verlag Ber

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41#
發(fā)表于 2025-3-28 16:54:17 | 只看該作者
Conference proceedings 2001ra, Portugal; 1997 in Providence, Rhode Island (USA); 1999 in Seeon, Germany), was held during 30 July – 2 August 2001 in Vancouver, Canada. ICCBR is the premier international forum for researchers and practitioners of case based reasoning (CBR). The objectives of this meeting were to nurture signif
42#
發(fā)表于 2025-3-28 21:04:22 | 只看該作者
Carl A. Goresky,Harry L. Goldsmithmers and whether a single or multiple retrievals were permitted. The experimental results suggest that the return set that optimizes benefit may be smaller for customer populations with little variation than for customer populations with wide variation.
43#
發(fā)表于 2025-3-29 01:54:21 | 只看該作者
D. T. Delpy,D. Parker,D. N. Halsalltion. It also presents our ongoing research on automatically deriving abstract indexing concepts from legal case texts. We report progress toward integrating IE techniques and ML for generalizing from case texts to our CBR case representation.
44#
發(fā)表于 2025-3-29 03:04:15 | 只看該作者
45#
發(fā)表于 2025-3-29 07:20:50 | 只看該作者
Ryuichiro Araki,Ichiro Nashimotoonly 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.
46#
發(fā)表于 2025-3-29 11:30:07 | 只看該作者
Acquiring Customer Preferences from Return-Set Selectionsmers and whether a single or multiple retrievals were permitted. The experimental results suggest that the return set that optimizes benefit may be smaller for customer populations with little variation than for customer populations with wide variation.
47#
發(fā)表于 2025-3-29 18:15:03 | 只看該作者
The Role of Information Extraction for Textual CBRtion. It also presents our ongoing research on automatically deriving abstract indexing concepts from legal case texts. We report progress toward integrating IE techniques and ML for generalizing from case texts to our CBR case representation.
48#
發(fā)表于 2025-3-29 20:18:58 | 只看該作者
49#
發(fā)表于 2025-3-30 02:21:45 | 只看該作者
A Case-Based Reasoning View of Automated Collaborative Filteringonly 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.
50#
發(fā)表于 2025-3-30 05:22:15 | 只看該作者
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