University of Massachusetts Boston

About: University of Massachusetts Boston is a education organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Health care. The organization has 6541 authors who have published 12918 publications receiving 411731 citations. The organization is also known as: UMass Boston.

Representation and Learning in Information Retrieval

Abstract: This dissertation introduces a new theoretical model for text classification systems, including systems for document retrieval, automated indexing, electronic mail filtering, and similar tasks. The Concept Learning model emphasizes the role of manual and automated feature selection and classifier formation in text classification. It enables drawing on results from statistics and machine learning in explaining the effectiveness of alternate representations of text, and specifies desirable characteristics of text representations. The use of syntactic parsing to produce indexing phrases has been widely investigated as a possible route to better text representations. Experiments with syntactic phrase indexing, however, have never yielded significant improvements in text retrieval performance. The Concept Learning model suggests that the poor statistical characteristics of a syntactic indexing phrase representation negate its desirable semantic characteristics. The application of term clustering to this representation to improve its statistical properties while retaining its desirable meaning properties is proposed. Standard term clustering strategies from information retrieval (IR), based on cooccurrence of indexing terms in documents or groups of documents, were tested on a syntactic indexing phrase representation. In experiments using a standard text retrieval test collection, small effectiveness improvements were obtained. As a means of evaluating representation quality, a text retrieval test collection introduces a number of confounding factors. In contrast, the text categorization task allows much cleaner determination of text representation properties. In preparation for the use of text categorization to study text representation, a more effective and theoretically well-founded probabilistic text categorization algorithm was developed, building on work by Maron, Fuhr, and others. Text categorization experiments supported a number of predictions of the Concept Learning model about properties of phrasal representations, including dimensionality properties not previously measured for text representations. However, in carefully controlled experiments using syntactic phrases produced by Church's stochastic bracketer, in conjunction with reciprocal nearest neighbor clustering, term clustering was found to produce essentially no improvement in the properties of the phrasal representation. New cluster analysis approaches are proposed to remedy the problems found in traditional term clustering methods.

Recommendations for designing and reviewing qualitative research in psychology: Promoting methodological integrity.

Abstract: The current paper presents recommendations from the Task Force on Resources for the Publication of Qualitative Research of the Society for Qualitative Inquiry in Psychology, a section of Division 5 of the American Psychological Association. This initiative was a response to concerns by authors that reviews of qualitative research articles frequently utilize inflexible sets of procedures and provide contradictory feedback when evaluating acceptability. In response, the Task Force proposes the concept of methodological integrity and recommends its evaluation via its two composite processes: (a) fidelity to the subject matter, which is the process by which researchers develop and maintain allegiance to the phenomenon under study as it is conceived within their tradition of inquiry, and (b) utility in achieving research goals, which is the process by which researchers select procedures to generate insightful findings that usefully answer their research questions. Questions that guide the evaluation of these processes, example principles, and a flowchart are provided to help authors and reviewers in the process of both research design and review. The consideration of methodological integrity examines whether the implementation of fidelity and utility function coherently together. Researchers and reviewers also examine whether methods further the research goals, are consistent with researchers’ approaches to inquiry, and are tailored to the characteristics of the subject matter and investigators. This approach to evaluation encourages researchers and reviewers to shift from using standardized and decontextualized procedures as criteria for rigor toward assessing the underlying methodological bases for trustworthiness as they function within research projects.

Language Assessment and Development in Toddlers with Autism Spectrum Disorders

Abstract: One of the primary diagnostic criteria for the diagnosis of autism spectrum disorders (ASD) is the presence of a language delay or impairment. Children with ASD are now being identified at significantly younger ages, and prior research has consistently found that early language skills in this population are heterogeneous and an important predictor for later outcome. The goal of this study was to systematically investigate language in toddlers with ASD and to identify early correlates of receptive and expressive language in this population. The study included 164 toddlers with ASD between the ages of 18 and 33 months who were evaluated on several cognitive, language and behavioral measures. Results suggested good agreement among different measures of early language, including direct assessment and parent report measures. Significant concurrent predictors of receptive language included gestures, non-verbal cognitive ability and response to joint attention. For expressive language, the most significant predictors were non-verbal cognitive ability, gestures and imitation. These findings have important implications for intervention programs targeting this population.