Although it has a relatively short history, conceptual clustering is an especially active area of research in machine learning. There are a variety of ways in which conceptual patterns (the Al contribution to clustering) play a role in the clustering process. Two distinct conceptual clustering paradigms (conceptual sorting of exemplars and concept discovery) are described briefly. Then six type...

The learning algorithm CLASSITALL is a module of DIA-MOLE, a tool that supports an engineeringoriented approach towards dialogue modelling for a spoken-language interface. CLASSITALL is a descendant of the COBWEB conceptual clustering algorithm, and in this paper we especially focus on extensions that are necessary for processing data within a spoken language system environment. While most lear...

In order to integrate a wide variety of databases or many diverse sources of information, we need the ability to learn the similarities directly from instances of the data, which may be embodied within a database model, a conceptual schema, application programs, or data contents. The process of determining semantically equivalent data items can not be "pre-programmed" since the information to b...

Patients with Alzheimer's disease (AD) have been found to be relatively dependent on familiarity in their recognition memory judgments. Conceptual fluency has been argued to be an important basis of familiarity. This study investigated the extent to which patients with mild AD use conceptual fluency cues in their recognition decisions. While no evidence of recognition memory was found in the pa...

The study aimed at identifying and analyzing the meaning of concept according to Deleuze, in Philosophy, and Rodgers, in Nursing. Based on an extract of reality, Deleuze creates the concept and calls it "plan of immanence". For Rodgers, in nursing, the concept emerges at the actual moment one wishes to construct the conceptual bases for Nursing. The authors demonstrate that, although Deleuze an...

The acquisition of Belief verbs lags behind the acquisition of Desire verbs in children. Some psycholinguistic theories attribute this lag to conceptual differences between the two classes, while others suggest that syntactic differences are responsible. Through computational experiments, we show that a probabilistic verb learning model exhibits the pattern of acquisition, even though there is ...

This study, based on the expanded means–end chain (MEC) theory, proposes a logic deduction procedure for qualitative analyses as a conceptual structure for establishing information systems. Through the expressions of variable matrix and set theory, the illustrations of data collection and programming procedures reveal the logic deduction framework for analyzing the linkages of consumer value sa...

We introduce DLR ,̀ an extension of the n-ary propositionally closed description logic DLR to deal with attribute-labelled tuples (generalising the positional notation), projections of relations, and global and local objectification of relations, able to express inclusion, functional, key, and external uniqueness dependencies. The logic is equipped with both TBox and ABox axioms forming a DLR` k...

Although various methods have been proposed for pedestrian attribute recognition, most studies follow the same feature learning mechanism, \ie, a shared image to classify multiple attributes. However, this mechanism leads low-confidence predictions and non-robustness of model in inference stage. In paper, we investigate why is case. We mathematically discover that central cause optimal cannot m...