With the rapid emergence and proliferation of Internet and the trend of globalization, a tremendous number of textual documents written in different languages are electronically accessible online. Efficiently and effectively managing these textual documents written different languages is essential to organizations and individuals. Although poly-lingual text categorization (PLTC) can be approached as a set of independent monolingual classifiers, this naïve approach employs only the training documents of the same language to construct to construct a monolingual classifier and fails to utilize the opportunity offered by poly-lingual training documents. Motivated by the significance of and need for such a poly-lingual text categorization technique, we propose a PLTC technique that takes into account all training documents of all languages when constructing a monolingual classifier for a specific language. Using the independent monolingual text categorization (MnTC) technique as our performance benchmark, our empirical evaluation results show that our proposed PLTC technique achieves higher classification accuracy than the benchmark technique does in both English and Chinese corpora. In addition, our empirical results also suggest the robustness of the proposed PLTC technique with respect to the range of training sizes investigated.

Thesis (Ph. D.)--University of California, San Diego and San Diego State University, 2008. / Title from first page of PDF file (viewed July 9, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 105-118).

Thesis (M.A.)--Miami University, Dept. of Speech Pathology and Audiology, 2004. / Title from first page of PDF document. Includes bibliographical references (p. 54-59).

This thesis examined how task demands shape the category representations formed through classification, inference and incidental learning. Experiments 1 to 3 examined the claim that the representations formed through inference learning are based only on the encoding of prototypical features (e.g., Yamauchi & Markman, 1998, 2000). Adults learned artificial categories through exemplar classification or feature inference. Inference learning either did or did not require attention to prototypical features. At test, all participants classified exemplars and inferred the values of missing features. Classification learning resulted in the encoding of both prototypical and atypical features. Inference learning also led to the representation of both prototypical and atypical features when attention to both was required during learning. Experiment 4 extended these results to inferences about novel items varying in similarity to training items. Inference learners required to attend to prototypical and atypical features during training were more sensitive to exemplar similarity when making novel inferences than those who attended only to prototypical features. Experiment 5 examined developmental change in the impact of noun and feature labels on feature inferences. Adults, 7-year-olds, and 5-yearolds were shown pairs of base and target exemplars. The base was given a noun or feature label. Participants were asked to predict the value of a missing feature of the target, when it was given the same or a different label as the base. Both adults and children were more likely to make inferences based on noun than feature labels. Hence, by five years of age, children grasp the inductive potential of noun labels. Experiments 6 to 9 compared incidental category learning with intentional classification. Adults classified categories of geometric shapes or learned the categories through an incidental task. Incidental recognition learning resulted in a broader allocation of attention than classification learning. Performing recognition before classification resulted in a broader attentional allocation than performing recognition after classification. Together with the results from mathematical modelling, these findings support a view of category learning in which the specific attentional demands of different learning tasks determine the nature of the category representations that are acquired.

Thesis (Ph. D.)--University of Washington, 1984. / Vita. Bibliography: leaves [108]-114.

Categorization is a fundamental process that underlies much of cognition. People form categories that allow them to generalize to and make inferences about novel objects and events. Current accounts of category learning suggest that there are two systems for learning categories, an explicit rule-based system that depends on frontal-striatal loops and working memory, and a procedural system that learns implicitly and depends on the tail of the caudate nucleus and occipital regions. In the present thesis, I propose that an additional declarative category learning system exists that is recruited to learn categories that are associated with multiple conjunctive and explicit, but not strictly rule-based, representations. The basis of the declarative category learning system is then tested in several behavioral and physiological recording experiments. The first issue that is examined in relation to the declarative category learning system is how subjects’ ability to encode stimuli affects their ability to form new flexible conjunctive representations. I provide evidence consistent with the idea that there are two ways to encode stimuli in category learning, either as a conjunction of individual parts or as holistic images. Forming part-based representations is found to be especially critical for forming new conjunctive representations for exceptions in brief single session experiments. A second question is how emotional processes interact with the declarative category learning system. Numerous lines of evidence suggest that emotional processes strongly affect learning and behavior. In a study using skin conductance, I find that anticipatory emotions (i.e., emotions present before a behavioral response) show a pattern consistent with orienting attention to behaviorally significant or potentially novel events. A final fMRI project ties together hypotheses about anticipatory emotions and encoding to their neural basis and provides a test of the predicted mapping of the declarative category learning system to the brain. By relating quantitative predictions from SUSTAIN, a model that shares relationships to the medial temporal lobes (MTL) and declarative category learning system, to fMRI data, I find clusters in an MTL-midbrain-PFC network that show patterns of activation consistent with recognizing exception items and updating these representations in response to error or surprise. / text

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Understanding how organisms learn perceptual categories on the basis of experience has been an important goal for researchers in a number of subdisciplines of psychology, including behavior analysis, experimental psychology, and comparative cognition. The primary aim of this thesis is to investigate how nonhumans (pigeons) and humans learn to make visual category judgments when stimuli vary quantitatively along two dimensions, particularly when accurate responding requires integration of information from both dimensions. The thesis consists of four chapters and a technical appendix. Chapter 1 is a literature review which provides a broad overview of studies on categorization by nonhumans and humans, as well as specific background for the current research. Chapters 2 and 3 constitute the empirical portion of this thesis. Four experiments are described, using a category task based on the ‘randomization’ procedure developed originally by Ashby and Gott (1988) with human participants and employed in subsequent research by Ashby, Maddox and their colleagues (see Ashby & Maddox, 2005; Maddox & Ashby, 2004, for review). Stimuli were Gabor patches that varied in frequency and orientation. Our primary goals were to determine whether pigeons could respond accurately in an information integration task with dimensionally-separable stimuli, and to compare performances of pigeons and humans. Chapter 2 reports two experiments with pigeons. Experiment 1 compared performance in two conditions which varied in terms of whether accurate performance required control by both dimensions (“information integration; II) or by a single dimension (“rule based”; RB). Results showed that pigeons learned both category tasks,with an average percentage of correct responses of 85.5% and 82% in the II and RB conditions, respectively. Although perfect performance was possible, responding for all pigeons fell short of optimality. Model comparison analyses showed that the General Linear Classifier (GLC; Ashby, 1992), which has been proposed to account for category learning in similar tasks with humans, provided a better account of responding in the II conditions, but a unidimensional model that assumed control only by frequency provided a better account of results from the RB condition. Thus results show that pigeons can respond accurately in an information integration task based on dimensionally-separable stimuli. However, analysis of residuals showed that systematic deviations of GLC predictions from the obtained data were present in both II and RB conditions. Specifically, accuracy for one category (A) was an inverted-U shaped function of orientation, whereas accuracy for the other category (B) did not vary systematically with orientation. Results from the RB condition showed evidence of an interaction between frequency and orientation, such that accuracy was higher for orientation values that were relatively low (i.e. close to horizontal) than high (i.e., close to vertical). Experiment 2 compared responding in two RB conditions which differed in terms of whether frequency or orientation was the relevant dimension. Pigeons again responded accurately in the task. Results from the frequency-relevant condition replicated the interaction obtained in Experiment 1, whereas results from the orientation-relevant condition gave no evidence of an interaction. Chapter 3 reports two experiments which compare performances of pigeons (Experiment 1) and humans (Experiment 2) in category tasks using identical stimuli. In each experiment there were two conditions, both based on the information-integration task in which the range of orientation values was wide or narrow. There were two primary goals. First, we wanted to test whether the inverted-U shaped pattern for Category A accuracy as a function of orientation would be replicated with different pigeons and stimulus values. Second, we wanted to compare responding of pigeons and humans. A secondary aim was to test whether restriction of range would affect control by orientation. Results from the condition with a wide orientation range were similar to those from Chapter 2, and showed that the inverted-U shaped pattern was replicated for both pigeons and humans. When the range of orientation values was narrow, responding for both pigeons and humans was exclusively controlled by orientation. Overall, results for pigeons and humans were similar and suggest that a common process may underlie information-integration category learning in both species. Chapter 4 provides a summary of the empirical results from Chapters 2 and 3, and shows that the inverted-U shaped pattern of accuracy for Category A as a function of orientation is unanticipated by current models for category learning, such as the GLC, prototype theory, and exemplar theory. A new ‘fuzzy prototype’ model is described which provides a good account of the results and predicts the inverted-U shaped pattern. According to the new model, subjects associate a linear segment in the stimulus space (‘fuzzy prototype’) with one of the category responses. When a stimulus is presented on a trial, subjects are assumed to use an ‘A/Not-A’ decision rule, with the probability of a Category A response determined as a function of the minimum distance of the stimulus from the fuzzy prototype. Possible directions for future research are considered. The thesis concludes with a technical appendix which describes the experimental chambers, interface hardware, and computer software developed to conduct the research,and a detailed user’s manual for the software. The system allows the same control procedure for both human and pigeon experiments, and should be useful for future research on categorization

This study was an investigation of the role of perceptual and functional features in the development of naturally-occurring and artifactual categories. Twenty-five college students, 16 fourth grade students, and 18 second-grade students participated in a sentence verification task. Each subject was presented sentences containing typical and atypical exemplars from naturally-occurring and artifactual categories paired with perceptual and functional features. The subjects were to indicate whether each sentence was true or false. A four-way mixed design ANOVA was performed on response times and error rates. A general developmental trend in category acquisition was indicated by the data. Children first learn typical naturallyoccurring category items. As they grow older, naturally-occurring categories are learned most thoroughly because of their clear-cut membership. Artifactual categories, which are less limited in membership, take longer for children to process. There was no evidence in the data to suggest that the differences between the two category types was due to a perceptual feature basis for naturally-occurring categories.

This thesis explores various aspects of children's understanding of similarity and difference and of the terms 'same' and 'different'. Understanding of 'same' appeared to be good but there was some evidence that it might not be complete. Understanding of 'different' was clearly inferior to that of 'same' and some children misinterpreted it as meaning 'same', this being supported by an experiment looking at interpretations of 'same', 'different' and a nonsense word, following Carey. Awareness of similarity and difference was investigated in several experiments. Subjects were required to give a similarity or a difference between two items, either named or pictured, in experiments developed from Claparede's work; they had to select from an array of items one either the same as or different from a target item and to justify that choice; and they had to judge whether two items were the same or not or were different or not in an experiment similar to one devised by Vurpillot. The children found more difficulty with similarity than with difference. It was suggested that similarity was typically handled in a holistic fashion, by a process of analogy, while difference was treated by analysis into component parts. The ability to analyse similarity developed with age. If similarity is not analysed into component points, these points cannot be mentioned in responses. An information-processing model of awareness was used to explain perseverative responses and the giving of differences when similarities were requested. It was suggested that these resulted in part from a failure to make transitions in awareness between different levels appropriately.