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Andrea L. Houston

Other affiliations: University of Arizona
Bio: Andrea L. Houston is an academic researcher from Louisiana State University. The author has contributed to research in topics: The Internet & Thesaurus (information retrieval). The author has an hindex of 9, co-authored 13 publications receiving 631 citations. Previous affiliations of Andrea L. Houston include University of Arizona.

Papers
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Journal ArticleDOI
TL;DR: The results indicate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclectic Internet information space into manageable sub-spaces that users can successfully navigate to locate a homepage of interest to them.
Abstract: The Internet provides an exceptional testbed for developing algorithms that can improve browsing and searching large information spaces. Browsing and searching tasks are susceptible to problems of information overload and vocabulary differences. Much of the current research is aimed at the development and refinement of algorithms to improve browsing and searching by addressing these problems. Our research was focused on discovering whether two of the algorithms our research group has developed, a Kohonen algorithm category map for browsing, and an automatically generated concept space algorithm for searching, can help improve browsing and/or searching the Internet. Our results indicate that a Kohonen self-organizing map (SOM)-based algorithm can successfully categorize a large and eclectic Internet information space (the Entertainment subcategory of Yahool) into manageable sub-spaces that users can successfully navigate to locate a homepage of interest to them. The SOM algorithm worked best with browsing tasks that were very broad, and in which subjects skipped around between categories. Subjects especially liked the visual and graphical aspects of the map. Subjects who tried to do a directed search, and those that wanted to use the more familiar mental models (alphabetic or hierarchical organization) for browsing, found that the map did not work well. The results from the concept space experiment were especially encouraging. There were no significant differences among the precision measures for the set of documents identified by subject-suggested terms, thesaurus-suggested terms, and the combination of subject- and thesaurus-suggested terms. The recall measures indicated that the combination of subject- and thesaurus-suggested terms exhibited significantly better recall than subject-suggested terms alone. Furthermore, analysis of the homepages indicated that there was limited overlap between the homepages retrieved by the subject-suggested and thesaurus-suggested terms. Since the retrieved homepages for the most part were different, this suggests that a user can enhance a keyword-based search by using an automatically generated concept space. Subjects especially liked the level of control that they could exert over the search, and the fact that the terms suggested by the thesaurus were real (i.e., originating in the homepages) and therefore guaranteed to have retrieval success.

299 citations

Journal ArticleDOI
TL;DR: Examination of generational differences in the work commitments of Baby Boomer and Gen-X information technology (IT) professionals suggests that these generations of IT professionals are more homogeneous than different.
Abstract: The study presented in this paper examines generational (age-cohort) differences in the work commitments of Baby Boomer (born between 1946 and 1962) and Gen-X (born between 1963 and 1981) information technology (IT) professionals. Data were obtained from 382 IT workers in 23 state agencies and universities. The work commitments examined include work involvement, job involvement, work group attachment, organizational commitment and professional commitment. Contrary to profiles of these two generations common in the popular and business press, results suggest that the work commitments of these generations of IT professionals are more homogeneous than different. Implications for research and for IT management are offered.

102 citations

Journal ArticleDOI
TL;DR: An architecture for medical knowledge information systems that will permit data mining across several medical information sources is proposed and a suite of data mining tools that are developing to assist NCI in improving public access to and use of the vast cancer information collections are discussed.
Abstract: This paper discusses several data mining algorithms and techniques that we have developed at the University of Arizona Artificial Intelligence Lab. We have implemented these algorithms and techniques into several prototypes, one of which focuses on medical information developed in cooperation with the National Cancer Institute (NCI) and the University of Illinois at Urbana-Champaign. We propose an architecture for medical knowledge information systems that will permit data mining across several medical information sources and discuss a suite of data mining tools that we are developing to assist NCI in improving public access to and use of their existing vast cancer information collections.

59 citations

Journal ArticleDOI
TL;DR: An experiment with an Al-based software agent shows that it can help users organize and consolidate ideas from electronic brainstorming as effectively as experienced human meeting facilitators and in a fifth of the time.
Abstract: Groupware has produced measurable productivity gains for major corporations in recent years. Agent software enhances productivity even more by helping groupware perform convergent tasks, thus freeing users for more creative work. An experiment with an Al-based software agent shows that it can help users organize and consolidate ideas from electronic brainstorming. The agent recalled concepts as effectively as experienced human meeting facilitators and in a fifth of the time.

53 citations

Journal ArticleDOI
27 Dec 2000
TL;DR: The preliminary results indicated that recall could be significantly improved by using a combined thesaurus approach, and there was almost no overlap of relevant terms suggested by the different thesauri for a given search.
Abstract: This research investigated the application of techniques successfully used in previous information retrieval research, to the more challenging area of medical informatics. It was performed on a biomedical document collection testbed, CANCERLIT, provided by the National Cancer Institute (NCI), which contains information on all types of cancer therapy. The quality or usefulness of terms suggested by three different thesauri, one based on MeSH terms, one based solely on terms from the document collection, and one based on the Unified Medical Language System (UMLS) Metathesaurus, was explored with the ultimate goal of improving CANCERLIT information search and retrieval. Researchers affiliated with the University of Arizona Cancer Center evaluated lists of related terms suggested by different thesauri for 12 different directed searches in the CANCERLIT testbed. The preliminary results indicated that among the thesauri, there were no statistically significant differences in either term recall or precision. Surprisingly, there was almost no overlap of relevant terms suggested by the different thesauri for a given search. This suggests that recall could be significantly improved by using a combined thesaurus approach.

42 citations


Cited by
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09 Mar 2012
TL;DR: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems as mentioned in this paper, and they have been widely used in computer vision applications.
Abstract: Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

2,069 citations

Journal ArticleDOI
TL;DR: This paper surveys the research in the area of Web mining, point out some confusions regarded the usage of the term Web mining and suggest three Web mining categories, which are then situate some of the research with respect to these three categories.
Abstract: With the huge amount of information available online, the World Wide Web is a fertile area for data mining research. The Web mining research is at the cross road of research from several research communities, such as database, information retrieval, and within AI, especially the sub-areas of machine learning and natural language processing. However, there is a lot of confusions when comparing research efforts from different point of views. In this paper, we survey the research in the area of Web mining, point out some confusions regarded the usage of the term Web mining and suggest three Web mining categories. Then we situate some of the research with respect to these three categories. We also explore the connection between the Web mining categories and the related agent paradigm. For the survey, we focus on representation issues, on the process, on the learning algorithm, and on the application of the recent works as the criteria. We conclude the paper with some research issues.

1,699 citations

Journal ArticleDOI
TL;DR: L'A.
Abstract: L'A. passe en revue les techniques de visualisation utilisees pour representer de facon cartographique la structure de domaine des disciplines scientifiques, et pour soutenir la recherche d'information et la classification. Un bref historique montre que la visualisation des domaines de connaissances s'enracine dans des disciplines telles que la scientometrie, la bibliometrie et l'analyse de citations, ainsi que la visualisation scientifique. L'A. analyse les principales etapes du processus de visualisation des domaines de connaissances : unites d'analyse, mesures, similarites entre unites. Differentes techniques couramment utilisees pour l'analyse et la visualisation des connaissances sont passees en revue : techniques de reduction de la dimensionnalite, analyse par clusters, configuration spatiale, visualisation et conception d'interaction. Differentes approches sont appliquees pour engendrer et comparer diverses representations cartographiques de la recherche sur la visualisation des domaines de connaissances. Ces cartes mettent en valeur les relations entre l'analyse de citations, la bibliometrie, la semantique et la visualisation de l'information. Augmenter l'accessibilite de la visualisation des domaines aupres des non-experts, appliquer la visualisation des domaines de connaissances pour mieux repondre a des questions pragmatiques, favoriser la collaboration et la diffusion des resultats entre chercheurs, developper des algorithmes plus robustes, comptent parmi les directions de recherche les plus prometteuses.

1,304 citations

Journal ArticleDOI
TL;DR: The authors examined the work values of a nationally representative sample of U.S. high school seniors in 1976, 1991, and 2006 (N = 16,507) representing Baby Boomers, Generation X (GenX), and Generation Me (GenMe), also known as GenY, or Millennials).

1,224 citations

Journal ArticleDOI
TL;DR: The elaboration likelihood model is used to explain the persuasive effect of the proportion and quality depending on product involvement, which shows that as the proportion of negative online consumer reviews increases, high-involvement consumers tend to conform to the perspective of reviewers, depending on the quality of the negativeOnline consumer reviews.

1,000 citations