Titlebook: Case-Based Reasoning Research and Development; 24th International C Ashok Goel,M Belén Díaz-Agudo,Thomas Roth-Berghofe Conference proceedin

Dissonance

Case VII: 90° Change in Wind Directionng the case base by deleting entire cases, based solely on their competence contributions. Recent work proposed an alternative which compressed individual cases by selectively deleting their internal contents. Early studies of this approach, termed . (FFD), demonstrated that for suitable domains, su

DUCE

PHIL

Oil Resources: Facts and Conjectures, is highly competent in the global sense. In this paper, we address the compositional adaptation process (of which single case adaptation is a special case) during casebase maintenance by proposing a case competence model for which we propose a measure called retention score to estimate the retentio

ORBIT

HACK

拋棄的貨物

Case Representation and Similarity Assessment in the ,BACK Decision Support System, patient data, and evaluate how to carry out a similarity-based retrieval in order to find the best advice for patients. Specifically, we will show how heterogeneous data received at various frequencies can be captured in cases and used for personalized advice.

接觸

Angiogenesis

Concept Discovery and Argument Bundles in the Experience Web,with a clear positive and negative polarity to create the bundles of arguments. The argument bundles allow us to define a concept-wise satisfaction degree of a user query over a set of bundles using the notion of fuzzy implication, allowing the reuse experiences of other people to the needs a specific user.

聽寫

Inferring Student Coding Goals Using Abstract Syntax Trees,ng problems. Without requiring programmed expert knowledge, our system demonstrates that accurate retrieval is possible for basic problems. We expect that additional research will uncover more applications for this technology, including more effective intelligent tutoring systems.

發(fā)出眩目光芒

Similarity Metrics from Social Network Analysis for Content Recommender Systems,ress their own preferences either. Nevertheless, online judges collect a rich information about which problems have been attempted, and solved, by which users. In this paper we consider all this information as a ., and use social network analysis techniques for creating similarity metrics between problems that can be then used for recommendation.