By Hans-Dieter Burkhard, Ralf Berger (auth.), Rosina O. Weber, Michael M. Richter (eds.)
The foreign convention on Case-Based Reasoning (ICCBR) is the pre-eminent overseas assembly on case-based reasoning (CBR). ICCBR 2007 (http://www.iccbr.org./iccbr07/) used to be the 7th during this sequence, featuring the main major contributions within the box of CBR. The convention came about in Belfast, Northern eire, united kingdom, in the course of August 13-16, 2007. ICCBR and its sister meetings ECCBR (European convention on Case-Based Reasoning) exchange each year. ICCBR 2007 a sequence of six profitable overseas meetings formerly held in Sesimbra, Portugal (1995); windfall, Rhode Island, united states (1997); Seeon, Germany (1999); Vancouver, Canada (2001); Trondheim, Norway (2003); and C- cago, Illinois, united states (2005). the eu meetings on Case-Based Reasoning (ECCBR) have been held as ecu workshops in Kaiserslautern, Germany (1993); Chantilly, France (1994); Lausanne, Switzerland (1996); Dublin, eire (1998); and Trento, Italy (2000); and as ecu meetings in Aberdeen, united kingdom (2002); Madrid, Spain (2004); and Lykia global, Turkey (2006). Days one, , and 4 comprised shows and posters on theoretical and - plied CBR study. so as to emphasize the significance of purposes, the tra- tional day was once switched over into an application hung on the second one day, in the midst of the convention. Day 3 was once dedicated to 5 workshops: Case-Based Reasoning and Context-Awareness; Case-Based Reasoning within the overall healthiness Sciences; Textual Case-Based Reasoning: past Retrieval; Uncertainty and Fuzziness in Case- dependent Reasoning; and information Discovery and Similarity.
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Extra info for Case-Based Reasoning Research and Development: 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast, Northern Ireland, UK, August 13-16, 2007 Proceedings
The incrementally specified query can seem to degrade the prediction ratio and eﬃciency of the search process because it aggregates contents of multiple data items. However, clearly it can have better recall ratio. The prediction ratio can be alleviated by using the weights so that the results can be automatically rated and sorted by a similarity measure based on the weights. 37 0 0 0 0 Fig. 8. An Example of Feature Weight Adjustment problem can be caused if the refined query has more values because the number of data sources can be increased and some data sources do not provide multivalued queries so that the refined query can be translated to a number of data source-specific queries.
This situation is ameliorated by using collaborative filtering, which attempts to predict usefulness of as yet unseen items for an active user, by proposing items based on those previously rated by other users. The basic idea is to recommend a set of unseen items that are preferred by other users who have tastes similar to the active user. Thus, the drawbacks of content-based filtering can be addressed with a higher level of confidence. However, collaborative filtering cannot be applied directly to our case-based KS framework because more than one user-query case, stored in the case repository, may be similar to the active user query.
Other approaches to represent chemical compounds have been proposed. For instance [14,19,12] represent the compounds as labeled graphs and this allows 38 E. Armengol Fig. 2. Partial view of the chemical ontology the use of graph search algorithms for detecting frequent substructures of the molecules in the same class. Particularly interesting are SUBDUE  and SMILES  that follow this approach. A completely diﬀerent approach was introduced in  where the compounds are organized according to their active centers (chemically identified with weak bonds).