Information Retrieval List Digest 141 (December 8, 1992) URL = http://hegel.lib.ncsu.edu/stacks/serials/irld/irld-141 IRLIST Digest ISSN 1064-6965 December 8, 1992 Volume IX, Number 45 Issue 141 ********************************************************** I. NOTICES C. Miscellaneous 1. HPCC Workshop Report on Vision, Speech and Natural Language Processing, and AI III. JOB ANNOUNCEMENTS 1. Catalog Librarian, Georgia College 2. Applications Engineer, Synopsys Inc. IV. PROJECT WORK C. Abstracts 1. IR-Related Dissertation Abstracts ********************************************************** I. NOTICES I.C.1. Fr: Benjamin W. Wah Re: HPCC Workshop Report on Vision, Speech and Natural Language Processing, and AI This message contains the executive summary of our Workshop on HPCC for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing, and Artificial Intelligence. The entire report (48 pages) can be obtained by anonymous ftp from manip.crhc.uiuc.edu (128.174.197.211) in directory /pub/hpcc. There are three files in this directory. text.ps PostScript version of the entire article text.ascii ASCII version of the entire article text.me file that can be processed by tbl, eqn, ditroff, and psdit to generate the PostSscript file. Please let me know if you have questions regarding this article. Benjamin W. Wah Professor Coordinated Science Laboratory University of Illinois, Urbana-Champaign (217) 333-3516 wah@manip.crhc.uiuc.edu ******************** Report on Workshop on High Performance Computing and Communications for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing, and Artificial Intelligence 1. EXECUTIVE SUMMARY: This article reports the findings of the Workshop on High Performance Com- puting and Communications (HPCC) for Grand Challenge Applications: Computer Vision, Speech and Natural Language Processing (SNLP), and Artificial Intelli- gence (AI). The goals of the workshop are to identify applications, research problems, and designs of HPCC systems for supporting applications in these areas. In computer vision, we have identified the main scientific issues as machine learning, surface reconstruction, inverse optics and integration, model acquisition, and perception and action. Since vision algorithms operate in dif- ferent levels of granularity, computers for supporting these algorithms need to be heterogeneous and modular. Advances in technology, new architectural con- cepts, and software design methods are essential for this area. In SNLP, we have identified issues in statistical analysis in corpus-based speech and language understanding, search strategies for language analysis, auditory and vocal-tract modeling, integration of multiple levels of speech and language analyses, and connectionist systems. Similar to algorithms in computer vision, algorithms in SNLP require high computational power, ranging from gen- eral purpose supercomputing to special purpose VLSI systems. As processing has various requirements, a hybrid heterogeneous computer system is the most desir- able. In AI, important issues that need immediate attention include the develop- ment of efficient machine learning and heuristic search methods that can adapt to different architectural configurations, and the design and construction of scalable and verifiable knowledge bases, active memories, and artificial neural networks. A computer system for supporting AI applications is heterogeneous, requiring research in high speed computer networks, mass storage and efficient retrieval methods, computer languages, and hardware and software design tools. Research in these areas is inherently multidisciplinary and will require active participation of researchers in device and networking technologies, sig- nal processing, computer architecture, software engineering, and knowledge engineering. Besides extending current frontiers in research, an important aspect to be emphasized is the integration of existing components and results into working systems. ********************************************************** III. JOB ANNOUNCEMENTS III.1. Fr: Scw@USCN Re: Position Announcement LIBRARY: Catalog Librarian. (Twelve month, tenure track faculty position) Responsible for cataloging and classifying titles added to collection using the OCLC system and participating in catalog revision. Supervises catalog assistants. Some original cataloging. Regularly scheduled reference duty. Qualifications: ALA-accredited MLS; knowledge of AACR2 and LC Subject Headings, LC Classification practices, and MARC format. Strong oral and written communication skills. Previous OCLC cataloging experience and working knowledge of MS-DOS computers desirable. A second Master's and/or doctorate required for promotion and tenure. Minimum: $24,000, dependent on qualifications and experience. Deadline: January 31, 1993 or until filled. Send letter of application, resume, transcripts, and three letters of refernce to Ms. Carolyn Boswell, Russell Library, Georgia College, Milledgeville, GA 31061. Georgia College is an AA/EOE Employer. GEORGIA COLLEGE: A residential comprehensive senior college of the University System of Georgia, comprised of five schools: Arts & Sciences, Business, Education, Nursing, and Graduate Studies. The College offers majors in more than 100 areas including undergraduate, graduate, and specialist degrees and, since its founding in 1889, has enjoyed an excellent reputation. It has a current enrollment of over 5,000 students with a full range of student activity and athletic programs. LOCATION: Georgia College is located in historic Milledgeville, Georgia, antebellum capital of Georgia. It is approximately 90 miles southeast of Atlanta and 30 miles northeast of Macon, in the center of the state. The city is the county seat and the metropolitan area of Milledgeville has a population of 38,000. Nearby Lake Sinclair provides many public recreational opportunities as well as those available at the College's lakefront facilities. There are modern health facilities, public and private schools, and successful businesses and industries which contribute to the area's growth. ********** III.1 Fr: Mitch Wyle Re: Applications Engineer, Network and Computing Services Synopsys Inc. Applications Engineer, Network and Computing Services Synopsys Inc., Mountain View, California 1. ROLE AND RESPONSIBILITY This position is chartered with o Organizing, procuring, developing, and maintaining a suite of information retrieval application systems that provide world class electronic customer support and connectivity to Synopsys o Systems administration tasks associated with the hardware and telecommunications infrastructure associated with the information retrieval project o Developing and maintaining a data classification system for use in the project o Identifying and articulating key customer issues for improving the systems. Success in the job during the first year will be measured in terms of o Quality of work on the project o Degree of dedication and energy invested in the project o Dedication to the improvement of the system and to customer support o A willingness to tackle tougher issues and broaden knowledge as the year progresses o Acquiring analytical capabilities necessary to identify key customer issues The Applications Engineer will report to the Manager of Network & Integration Services. 2. PROFESSIONAL BACKGROUND AND EXPERIENCE The most appropriate candidates will have: Software development experience from previous work MSEE & 1 year of work experience or BSEE & 2 years of work experience Supported customers in some capacity or have teaching experience Some exposure to full text retrieval and distributed bulletin board systems (WAIS, c-news, electronic mail subscription services) Additional positive qualities for which we are searching include + Outstanding written and verbal communications skills + Very strong team player + Strongly motivated to help people + Motivated by quality and excellence in all work + Strong interest in learning and growing + Japanese language abilities Compensation depends upon qualifacations of applicant and is flexible. Position is in Mt. View, California. Synopsys Inc. develops, markets and supports high-level design automation software for designers of integrated circuits and electronic systems. The Company currently offers a comprehensive set of synthesis, simulation and test tools, which are supported on the most widely used UNIX workstations. Mitch Wyle (415) 694 4076 (work) Synopsys Inc 700 E. Middlefield Rd. (415) 965 8637 (fax) Mountain View, CA 94043-4033 (800) 843 5669 x4076 (voice) wyle@synopsys.com ********************************************************** IV. PROJECT WORK IV.C.1. Fr: Susanne M. Humphrey Re: Selected IR-Related Dissertation Abstracts The following are citations selected by title and abstract as being related to Information Retrieval (IR), resulting from a computer search, using BRS Information Technologies, of the Dissertation Abstracts Online database produced by University Microfilms International (UMI). Included are UMI order number, title, author, degree, year, institution; number of pages, one or more Dissertation Abstracts International (DAI) subject descriptors chosen by the author, and abstract. Unless otherwise specified, paper or microform copies of dissertations may be ordered from University Microfilms International, Dissertation Copies, Post Office Box 1764, Ann Arbor, MI 48106; telephone for U.S. (except Michigan, Hawaii, Alaska): 1-800-521-3042, for Canada: 1-800-268-6090. Price lists and other ordering and shipping information are in the introduction to the published DAI. An alternate source for copies is sometimes provided. Dissertation titles and abstracts contained here are published with permission of University Microfilms International, publishers of Dissertation Abstracts International (copyright by University Microfilms International), and may not be reproduced without their prior permission. AN University Microfilms Order Number ADG92-06633. AU SCHLAGER, MARK STEVEN. TI AN ANALYSIS OF DATABASE QUERYING AS A COGNITIVE SKILL. IN University of Colorado at Boulder Ph.D. 1991, 136 pages. SO DAI V52(11), SecB, pp6116. DE Psychology, Experimental. AB The purpose of this dissertation was to extend cognitive theory to a new domain of investigation, database querying, and in doing so begin to understand the difficulties people face in a real-world task environment. These goals were achieved by observing people performing the task of querying a relational database, and analyzing their behavior in the context of the broader domain of word problems. The goals of people performing query tasks and the methods they used to accomplish those goals were captured by a GOMS task analysis model. The model addresses two stages of the query process: understanding the query, and following the appropriate procedures for solving the query. The former is the same for all instantiations of the task. The second stage, however, differs in the methods used for manual (paper-and-pencil) versus computerized querying and across query languages. In both the paper-and-pencil and computerized querying task, the information in the query statement is decomposed into the objects of the search (list items) and conditions placed on the search. These two types of information are combined with table names and other information derived from the database to form a query representation. In the paper-and-pencil task, the completed representation triggers the execution of table-searching strategies, which have been learned through prior experience. The particular strategy used depends upon which slots in the representation have been filled. In contrast, the computerized task requires the acquisition of query command-building strategies. The GOMS model yielded qualitative performance and transfer predictions. A production system cognitive simulation model was built to obtain quantitative performance predictions. The production system provided a detailed description of the query representation and search operations required to perform complex paper-and-pencil and computerized query tasks, and the knowledge structures from which these processes originate. An experiment was conducted to test the model's ability to predict competent performance, learning, and knowledge transfer. Subjects were trained on four types of queries, in both the computerized and paper-and-pencil mode. The results indicated that the model provided a good account of subjects' behavior on both the paper-and-pencil and computerized query tasks. (Abstract shortened with permission of author.). AN University Microfilms Order Number ADGNN-59876. AU MOORE, GALE. TI THE INFORMATION INDUSTRY IN ONTARIO: A TEST OF THE POST-INDUSTRIAL THESIS. IN University of Toronto (Canada) Ph.D. 1990, 411 pages. SO DAI V52(11), SecA, pp4111. DE Sociology, Social Structure and Development. IS ISBN: 0-315-59876-X. AB The general aim of this study is to evaluate the claim that post-industrial society is a new social formation discontinuous from industrial society that preceded it. Sociologically, the work of Daniel Bell remains the most systematic elaboration of this thesis. Bell's evidence to support the claim of social transformation comes primarily from changes in the social structure, in particular in the area of production, however the data advanced to support this claim are organized according to industrial principles. The key question that must be answered in evaluating any theory of social transformation is whether there is evidence of shifts in the bases of power. In any discussion of social transformation we assume that economic structures, in particular economic organizations can be studied for evidence of change away from industrial forms and relations of production. According to Bell the crucial variables of post-industrial society are information and knowledge that replace capital and labour. This results in a change in the system of stratification--the key division is between the scientific and technical workers and those outside. The major class of the new society is primarily a professional class, based on knowledge rather than property. To test the post-industrial thesis we adopt the strategy of the critical case, i.e., to select a locale most favourable to the validation of the thesis. A series of analytical models derived from the literature on post-industrialism and information society were used to locate an industry advanced in terms of the tenets of the post-industrial and information society concepts. The industry that emerged was the information industry. As the information industry does not exist in official industry statistics, a study of this industry represents pioneering work. We first analyse the industry in terms of its structure and the organizational structure of the firms that comprise it. We test the post-industrial hypothesis of the centrality of theoretical knowledge in terms of who works in the firms and the nature of their qualifications and ask whether the possession of expert knowledge provides a base for establishing jurisdiction over the division of labour. We look for evidence of the emergence of a collective occupational activity within the industry that would suggest an attempt to institutionalize expert knowledge and provide a base of power external to the firm. Finally, we test the hypothesis that experts in this industry have been able to use their knowledge as a base of power in terms of securing job control, occupational control and control in terms of the organization. We conclude that the increases in the numbers of professional and technical occupations predicted by Bell have occurred in the information industry but that there is little evidence to suggest the emergence of a professional and technical elite or a shift towards knowledge as a base of power in this industry at the present time. (Abstract shortened by UMI.). IRLIST Digest is distributed from the University of California, Division of Library Automation, 300 Lakeside Drive, Oakland, CA. 94612-3550. Send subscription requests to: LISTSERV@UCCVMA.BITNET Send submissions to IRLIST to: IR-L@UCCVMA.BITNET Editorial Staff: Clifford Lynch calur@uccmvsa.ucop.edu or calur@uccmvsa.bitnet Nancy Gusack ncgur@uccmvsa.bitnet Mary Engle meeur@uccmvsa.bitnet The IRLIST Archives will be set up for anonymous FTP, and the address will be announced in future issues. To access back issues presently, send the message INDEX IR-L to LISTSERV@UCCVMA.BITNET. 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