Special issue on advances in data mining and its applications

Data mining is the process to identify valid, implicit, previously unknown, potentially useful and understandable information from large databases. It is an important step in the process of knowledge discovery in databases, (Olaru & Wehenkel, 1999). In a data mining process, input data can be structured, seme-structured, or unstructured. Data can be in text, categorical or numerical values. One of the important characteristics of data mining is its ability to deal data with large volume, distributed, time variant, noisy, and high dimensionality. A large number of data mining algorithms have been developed for different applications. For example, association rules mining can be useful for market basket problems, clustering algorithms can be used to discover trends in unsupervised learning problems, classification algorithms can be applied in decision-making problems, and sequential and time series mining algorithms can be used in predicting events, fault detection, and other supervised learning problems (Vapnik, 1999). Classification is among the most important tasks in the data mining, particularly for data mining applications into engineering fields. Together with regression, classification is mainly for predictive modelling. So far, there have been a number of classification algorithms in practice. According to (Sebastiani, 2002), the main classification algorithms can be categorized as: decision tree and rule based approach such as C4.5 (Quinlan, 1996); probability methods such as Bayesian classifier (Lewis, 1998); on-line methods such as Winnow (Littlestone, 1988) and CVFDT (Hulten 2001), neural networks methods (Rumelhart, Hinton & Wiliams, 1986); example-based methods such as k-nearest neighbors (Duda & Hart, 1973), and SVM (Cortes & Vapnik, 1995). Other important techniques for classification tasks include Associative Classification (Liu et al, 1998) and Ensemble Classification (Tumer, 1996).

Associative priming in color naming: Interference and facilitation

In Experiment 1, color-naming interference for target stimuli following associated primes was greater in a group making a lexical decision to the prime than in a group reading the prime silently. High-frequency targets were responded to more quickly than low-frequency targets. In Experiment 2, with subjects naming the prime, there was evidence of associative interference when the prime and the target were grouped temporally but not when the intertrial interval was comparable with the prime-target interval. Associative primes presented at a short (120-msec) prime-target stimulus onset asynchrony facilitated color naming in Experiment 3. Taken together, the results suggest that the effect of faster processing of the base word in a color-naming task is facilitatory and that color-naming priming interference arises when associative prime processing increases conflict between word and color responses by enhancing phonological or articulatory activation of the base word.

Expectancy-based associative and identity priming in pronunciation

Evidence for expectancy-based priming in the pronunciation task was provided in three experiments. In Experiments 1 and 2, a high proportion of associatively related trials produced greater associative priming and superior retrieval of primes in a subsequent test of memory for primes, whereas high- and low-proportion groups showed comparable repetition benefits in perceptual identification of previously presented primes. In Experiment 2, the low-proportion condition had few associatively related pairs hut many identity pairs. In Experiment 3, identity priming was greater in a high- than a low-identity proportion group, with similar repetition benefits and prime retrieval responses for the two groups. These results indicate that when the prime-target relationship is salient, subjects strategically vary their processing of the prime according to the nature of the prime-target relationship.

Experimental manipulation of prior experience: Effects on item and associative recognition

Frequency of exposure to very low- and high-frequency words was manipulated in a three-phase (familiarisation, study, and test) design. During familiarisation, words were presented with their definition (once, four times, or not presented). One week (Experiment 1) or one day (Experiment 2) later, participants studied a list of homogeneous pairs (i.e., pair members were matched on background and familiarisation frequency). Item and associative recognition of high- and very low-frequency words presented in intact, rearranged, old-new, or new-new pairs were tested in Experiment 1. Associative recognition of very low-frequency words was tested in Experiment 2. Results showed that prior familiaris ation improved associative recognition of very low-frequency pairs, but had no effect on high-frequency pairs. The role of meaning in the formation of item-to-item and item-to-context associations and the implications for current models of memory are discussed.

Indefinite determiner introducing definite referent: a special use of 'yi 'one' + classifier' in Chinese

The indefinite determiner yi 'one'+ classifier' is the most approximate to an indefinite article, like the English a, in Chinese. It serves all the functions characteristic of representative stages of grammaticalization from a numeral to a generalized indefinite determiner as elaborated in the literature. It is established in this paper that the Chinese indefinite determiner has developed a special use with definite expressions, serving as a backgrounding device marking entities as of low thematic importance and unlikely to receive subsequent mentions in ensuing discourse. 'yi+ classifier' in the special use with definite expressions displays striking similarities in terms of semantic bleaching and phonological reduction with the same determiner at the advanced stage of grammaticalization characterized by uses with generics, nonspecifics and nonreferentials. An explanation is offered in terms of an implicational relation between nonreferentiality and low thematic importance which characterize the two uses of the indefinite determiner. While providing another piece of evidence in support of the claim that semantically nonreferentials and entities of low thematic importance tend to be encoded in terms of same linguistic devices in language, findings in this paper have shown how an indefinite determiner can undergo a higher degree of grammaticalization than has been reported in the literature-it expands its scope to mark not only indefinite but also definite expressions as semantically nonreferential and/or thematically unimportant. (C) 2003 Elsevier B.V. All rights reserved.

Gene-expression profiling reveals distinct expression patterns for classic versus variant Merkel cell phenotypes and new classifier genes to distinguish Merkel cell from small-cell lung carcinoma

Merkel cell carcinoma (MCC) is a rare aggressive skin tumor which shares histopathological and genetic features with small-cell lung carcinoma (SCLC), both are of neuroendocrine origin. Comparable to SCLC, MCC cell lines are classified into two different biochemical subgroups designated as 'Classic' and 'Variant'. With the aim to identify typical gene-expression signatures associated with these phenotypically different MCC cell lines subgroups and to search for differentially expressed genes between MCC and SCLC, we used cDNA arrays to pro. le 10 MCC cell lines and four SCLC cell lines. Using significance analysis of microarrays, we defined a set of 76 differentially expressed genes that allowed unequivocal identification of Classic and Variant MCC subgroups. We assume that the differential expression levels of some of these genes reflect, analogous to SCLC, the different biological and clinical properties of Classic and Variant MCC phenotypes. Therefore, they may serve as useful prognostic markers and potential targets for the development of new therapeutic interventions specific for each subgroup. Moreover, our analysis identified 17 powerful classifier genes capable of discriminating MCC from SCLC. Real-time quantitative RT-PCR analysis of these genes on 26 additional MCC and SCLC samples confirmed their diagnostic classification potential, opening opportunities for new investigations into these aggressive cancers.

Alcohol-related associative strength and drinking behaviours: concurrent and prospective relationships

The first part of this research assessed the longitudinal relationships between alcohol- related associative strength and alcohol use measured at two time- points, 6 months apart. Cross-lagged results support the utility of alcohol- related associative strength to predict drinking behaviours prospectively and vice versa. These results remained after competing explanations of previous use, autocorrelations between memory measures, sensation seeking and background variables of age and gender were accounted for. Findings offer further evidence for an implicit cognitions approach to drinking processes. In the second part of our study, cross-sectional analysis investigated potential mediating mechanisms in the relation of associative strength to quantity and frequency dimensions of drinking. Mediational models provide preliminary evidence that implicit memory processes may have differential effects on quantity and frequency dimensions of drinking behaviours. The results point to the possibility that increasing awareness of implicit alcohol-related associations may have utility in interventions for young adults.

Adolescent tobacco-related associative memory: a cross-sectional and contextual analysis

Tobacco use is prevalent in adolescents, and understanding factors that contribute to its uptake and early development remains a critical public health priority. Implicit drug-related memory associations (DMAs) are predictive of drug use in older samples, but such models have little application to adolescent tobacco use. Moreover, extant research on memory associations yields little information on contextual factors that may be instrumental in the development of DMAs. The present study examined (a) the degree to which tobacco-related memory associations (TMAs) were associated with concurrent tobacco use and (b) the extent to which TMAs mediated the association of peer and self-use. A sample of 210 Australian high school students was recruited. Participants completed TMA tasks and behavioral checklists designed to obscure the tobacco-related focus of the study. Results showed that TMAs were associated with peer use, and TMAs predicted self-use. We found no evidence that TMAs mediated the association of peer and self-use. Future research might examine the emotive valence of implicit nodes and drinking behavior. The results have implications for testing the efficacy of consciousness-raising interventions for adolescents at risk of tobacco experimentation or regular use.

Boosting the tree augmented naive bayes classifier

The Tree Augmented Naïve Bayes (TAN) classifier relaxes the sweeping independence assumptions of the Naïve Bayes approach by taking account of conditional probabilities. It does this in a limited sense, by incorporating the conditional probability of each attribute given the class and (at most) one other attribute. The method of boosting has previously proven very effective in improving the performance of Naïve Bayes classifiers and in this paper, we investigate its effectiveness on application to the TAN classifier.

Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics

Support vector machines (SVMs) have recently emerged as a powerful technique for solving problems in pattern classification and regression. Best performance is obtained from the SVM its parameters have their values optimally set. In practice, good parameter settings are usually obtained by a lengthy process of trial and error. This paper describes the use of genetic algorithm to evolve these parameter settings for an application in mobile robotics.

Acquisition of the English article system in SLA and the Missing Surface Inflection Hypothesis

This paper examines the article system in interlanguage grammar focusing on Japanese learners of English, whose native language lacks articles. It will be demonstrated that for the acquisition of the English article system, count/mass distinctions and definiteness are the crucial factors. Although Japanese does not employ the article system to encode these aspects, it will be argued that they are nevertheless syntactically encoded through its classifier system. Hence, the problem for these learners must be to map these features onto the appropriate surface forms as the Missing Surface Inflection Hypothesis predicts (Prévost & White 2000). This suggestion will further be supported empirically by a fill-in-the article task. It will be concluded that these Japanese learners understand the English article system fairly well, possibly due to their native language, yet have problems with realizing the relevant features (i.e. count/mass distinctions and definiteness) in the target language.

A framework for electricity price spike analysis with advanced data mining methods

There are many techniques for electricity market price forecasting. However, most of them are designed for expected price analysis rather than price spike forecasting. An effective method of predicting the occurrence of spikes has not yet been observed in the literature so far. In this paper, a data mining based approach is presented to give a reliable forecast of the occurrence of price spikes. Combined with the spike value prediction techniques developed by the same authors, the proposed approach aims at providing a comprehensive tool for price spike forecasting. In this paper, feature selection techniques are firstly described to identify the attributes relevant to the occurrence of spikes. A simple introduction to the classification techniques is given for completeness. Two algorithms: support vector machine and probability classifier are chosen to be the spike occurrence predictors and are discussed in details. Realistic market data are used to test the proposed model with promising results.

Calcium-permeable AMPA receptors mediate long-term potentiation in interneurons in the amygdala

Fear conditioning is a paradigm that has been used as a model for emotional learning in animals'. The cellular correlate of fear conditioning is thought to be associative N-methyl-D-aspartate (NMDA) receptor-dependent synaptic plasticity within the amygdala(1-3). Here we show that glutamatergic synaptic transmission to inhibitory interneurons in the basolateral amygdala is mediated solely by alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. In contrast to AMPA receptors at inputs to pyramidal neurons, these receptors have an inwardly rectifying current-voltage relationship, indicative of a high permeability to calcium(4 5), Tetanic stimulation of inputs to interneurons caused an immediate and sustained increase in the efficacy of these synapses. This potentiation required a rise in postsynaptic calcium, but was independent of NMDA receptor activation. The potentiation of excitatory inputs to interneurons was reflected as an increase in the amplitude of the GABAA-mediated inhibitory synaptic current in pyramidal neurons. These results demonstrate that excitatory synapses onto interneurons within a fear conditioning circuit show NMDA-receptor independent long-term potentiation. This plasticity might underlie the increased synchronization of activity between neurons in the basolateral amygdala after fear conditioning(6).