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<title>1990: Artificial intelligence and expert systems : will they change the library?</title>
<link>http://hdl.handle.net/2142/1209</link>
<description>27th Clinic on Library Applications of Data Processing. Edited by F.W. Lancaster and Linda C. Smith</description>
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<rdf:li resource="http://hdl.handle.net/2142/1303"/>
<rdf:li resource="http://hdl.handle.net/2142/1302"/>
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<rdf:li resource="http://hdl.handle.net/2142/1300"/>
<rdf:li resource="http://hdl.handle.net/2142/1299"/>
<rdf:li resource="http://hdl.handle.net/2142/1298"/>
<rdf:li resource="http://hdl.handle.net/2142/1297"/>
<rdf:li resource="http://hdl.handle.net/2142/1296"/>
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<item rdf:about="http://hdl.handle.net/2142/1303">
<title>Walking Your Talk: Why Information Managers are Not High Tech</title>
<link>http://hdl.handle.net/2142/1303</link>
<description>Walking Your Talk: Why Information Managers are Not High Tech

Penniman, W. David

This paper discusses the role of technology in creating successful&#13;
information services, and also the important role of people in creating&#13;
successful implementations of new technologies. Much has been written&#13;
about the areas of artificial intelligence and expert systems. This paper&#13;
will try to stay on a broader level, its ideas applying to a wide range&#13;
of technologies, well beyond the traditional library arena. Although&#13;
most readers of these proceedings are concerned with information&#13;
management within the library context, libraries provide an&#13;
environment well suited for a more general discussion about change&#13;
and the role of technology in introducing change necessary for survival.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1302">
<title>Expert Systems in Document Delivery: The Feasibility of Learning Capabilities</title>
<link>http://hdl.handle.net/2142/1302</link>
<description>Expert Systems in Document Delivery: The Feasibility of Learning Capabilities

Pontigo, Jaime

Tovar-Reyes, Ezequiel

Rodriguez, Guillermo

Ortiz-Gama, Sergio

To solve the problem of document delivery in Mexico, the authors&#13;
developed SEADO (Expert System for Document Supply). SEADO&#13;
consists of three main components: a knowledge base, an expert system&#13;
shell, and the database. The knowledge base was built through fault&#13;
tree analysis and through structured flowcharts. The shell was developed&#13;
with EXSYS, a generalized expert system development package. The&#13;
database was based on information sources of various kinds: printed&#13;
material, local databases, public databases, etc. To evaluate the impact&#13;
of different learning capabilities, the authors decided to test alternative&#13;
ways of achieving a predictor for the system to perform in a dynamic&#13;
and adaptive way. Learning by a weighted-based scheme was compared&#13;
with a probability-based scheme.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1301">
<title>Intelligent Interfaces to Online Databases</title>
<link>http://hdl.handle.net/2142/1301</link>
<description>Intelligent Interfaces to Online Databases

Vickery, Brian C.

The possible functions of intelligent interfaces are summarized. Five&#13;
examples of recent or current European projects on the development&#13;
of interfaces are described: INSERM, GIRT, EURISKO, ERLI/&#13;
MINITEL, and IMIS. A number of the problems of interface design&#13;
and implementation are reviewed.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1300">
<title>Knowledge Representation in Artificial Intelligence</title>
<link>http://hdl.handle.net/2142/1300</link>
<description>Knowledge Representation in Artificial Intelligence

Travis, Irene L.

The problems of knowledge representation and use in expert systems&#13;
and the problems of organizing and searching information in libraries&#13;
and other bibliographic systems have much in common. There are two&#13;
basic paradigms for representing knowledge in the knowledge bases&#13;
of expert systems: rule-based and object-based. Of the two, the rulebased&#13;
approach has had more publicity, but the object-oriented&#13;
approach, which will seem more familiar to librarians, is coming to&#13;
be seen as a necessary complement to rules or even as the more basic&#13;
system component. One of the principal unsolved problems in&#13;
knowledge representation is how to provide expert systems and natural&#13;
language processing systems with more world knowledge, particularly&#13;
"common sense" knowledge, in order to make them more robust. A&#13;
major project to build a knowledge base of such basic information is&#13;
underway at the Microelectronics and Computer Corporation (MCC),&#13;
a corporation financed by a consortium of American industry to carry&#13;
out research in advanced computing and computing technology. Since&#13;
the project represents an attempt to organize a very large and general&#13;
body of knowledge for use, it can be hypothesized that it will face many&#13;
of the same problems faced by librarians as they have done the same&#13;
thing. The project's published goals and achievements at the midpoint&#13;
of its ten-year life are reviewed from that perspective. Four barriers to&#13;
such efforts are discussed: (1) the variability of human performance&#13;
in tasks related to knowledge representation and search; (2) the paradox of structure; (3) the double-edged nature of the 80/20 rule; and (4) the&#13;
inertia of an installed base.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1299">
<title>Natural Language Processing: Current Status for Libraries</title>
<link>http://hdl.handle.net/2142/1299</link>
<description>Natural Language Processing: Current Status for Libraries

Warner, Amy J.

A general introduction to natural language processing is provided,&#13;
including a definition and an overview of how natural language&#13;
processing systems work. Representative systems from both the research&#13;
and applied sectors are presented in order to illustrate the state of the&#13;
art in the field and the issues which underlie system design and&#13;
implementation. Actual and potential areas for natural language&#13;
processing in information retrieval, including retrieval from online&#13;
catalogs, indexes, and full texts are discussed, with an assessment of&#13;
short- and long-range agendas and possible limitations.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1298">
<title>User Models for Information Systems: Prospects and Problems</title>
<link>http://hdl.handle.net/2142/1298</link>
<description>User Models for Information Systems: Prospects and Problems

Borgman, Christine L.

Plute, Yolanda I.

Expert systems attempt to model multiple aspects of human-computer&#13;
interaction, including the reasoning of the human expert, the knowledge&#13;
base, and characteristics and goals of the user. This paper focuses on&#13;
models of the human user that are held by the system and utilized in&#13;
interaction, with particular attention to information retrieval&#13;
applications. User models may be classified along several dimensions,&#13;
including static vs. dynamic, stated vs. inferred, and short-term vs. longterm&#13;
models. The choice of the type of model will depend on a number&#13;
of factors, including frequency of use, the relationship between the user&#13;
and the system, the scope of the system, and the diversity of the user&#13;
population. User models are most effective for well-defined tasks,&#13;
domains, and user characteristics and goals. These user-system aspects&#13;
tend not to be well defined in most information retrieval applications.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1297">
<title>Expert Systems at the National Agricultural Library: Past, Present, and Future</title>
<link>http://hdl.handle.net/2142/1297</link>
<description>Expert Systems at the National Agricultural Library: Past, Present, and Future

Waters, Samuel T.

Since 1986, the National Agricultural Library (NAL) has developed four&#13;
expert advisory systems for ready reference on agricultural topics, and&#13;
has trained librarians from other institutions who have contributed&#13;
three other systems. All may be downloaded from the NAL electronic&#13;
bulletin board. NAL has stimulated development elsewhere of several&#13;
reference advisors in subjects other than agriculture, and has actively&#13;
promoted interest in the use of expert systems in libraries. NAL has&#13;
been responsible for the development of an "intelligent document" in&#13;
the field of aquaculture, which uses hypertext and contains an expert&#13;
system. Similar products in several other fields are underway. "Smart"&#13;
courseware is also being developed for library training. In the future,&#13;
NAL may explore the use of new artificial intelligence techniques such&#13;
as neural networks, will increase development of multimedia products&#13;
and use of multifunctional software, working toward the development&#13;
of knowledge access and utilization systems in important areas of concern&#13;
in agriculture.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1296">
<title>Reference Expert Systems: Foundations in Reference Theory</title>
<link>http://hdl.handle.net/2142/1296</link>
<description>Reference Expert Systems: Foundations in Reference Theory

Parrott, James R.

A reference expert system may be considered to be a system with a&#13;
knowledge base covering various aspects of the reference process in a&#13;
library setting. Knowledge bases generally consist of several components&#13;
(such as databases, rule bases, frames, and semantic nets) that interact&#13;
with an inference engine, a user interface, and each other. This paper&#13;
will examine progressively more complex knowledge-based systems for&#13;
reference that can be constructed from components like these,&#13;
concentrating at first on combinations of databases and rule bases. This&#13;
examination will lead to a classification of reference expert systems.&#13;
In Section 3, very simple architectures of a type common in other&#13;
fields will first be considered. Arguments drawn from reference theory&#13;
suggest that these simple architectures are appropriate primarily in&#13;
dealing with directional reference transactions. In Sections 4 and 5,&#13;
reference theory will be used to develop two additional architectures&#13;
more appropriate to other reference transactions, such as ready-reference&#13;
transactions. The classification of reference expert systems will be&#13;
completed in Section 6 by examining further reference theory and then&#13;
using it to develop variants on the three basic types. Section 7.1 will&#13;
discuss briefly the use of reference knowledge bases for computer-assisted&#13;
instruction. Section 7.2 will consider deep reference knowledge. The&#13;
paper will conclude with some prognostications about future&#13;
developments.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1295">
<title>Interactive Knowledge-Based Systems for Improved Subject Analysis and Retrieval</title>
<link>http://hdl.handle.net/2142/1295</link>
<description>Interactive Knowledge-Based Systems for Improved Subject Analysis and Retrieval

Humphrey, Susanne M.

A knowledge-based, or expert, system encoding both factual and&#13;
procedural knowledge to assist users in performing an intellectual task&#13;
is ideally suited to indexing. Existing thesauri, classification schemes,&#13;
and indexing manuals are a good starting point, and artificial&#13;
intelligence (AI) computer languages and data structures seem well suited&#13;
for development of these systems. In addition, currently available&#13;
workstation environments (with windows and mouse) and standard&#13;
software (such as X Windows) should make possible sophisticated and&#13;
portable interfaces. A unique prototype, the MedlndEx System, is being&#13;
developed to assist people using the Medical Subject Headings (MeSH )&#13;
thesaurus to index the MEDLINE database in MEDLARS (Medical&#13;
Literature Analysis and Retrieval System) at the National Library of&#13;
Medicine (NLM). MedlndEx is, in principle, applicable to any indexing&#13;
system using a thesaurus and following a body of indexing rules.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
</item>
<item rdf:about="http://hdl.handle.net/2142/1294">
<title>Automated Cataloging: Implications for Libraries and Patrons</title>
<link>http://hdl.handle.net/2142/1294</link>
<description>Automated Cataloging: Implications for Libraries and Patrons

Weibel, Stuart L.

Many changes in cataloging practice have been and will increasingly&#13;
be technology driven. Bound lists and drawers of cards defined the form&#13;
and function of catalogs for as long as they existed until the advent&#13;
of digital computers. Even today, however, MARC records are as much&#13;
a derivative of catalog cards as the reverse. The additional functionality&#13;
of computer catalogs affords opportunities to increase the effectiveness&#13;
of the cataloging process and improve the value of the catalog itself.&#13;
Three main research areas are examined with regard to their anticipated&#13;
influence on this evolution. Automated cataloging research, focusing&#13;
on the application of rule-based systems to cataloging, represents a novel&#13;
way to address the cataloging process per se, but has as yet made only&#13;
modest progress. The incremental implementation of a variety of&#13;
computer-assisted methods for addressing aspects of cataloging&#13;
represents a second, more conventional approach to advancing the state&#13;
of the art in cataloging automation. This approach shares the goal&#13;
of the first to build intelligent capabilities into cataloging systems&#13;
but the focus remains on human cataloging systems and the methods&#13;
of implementation are more conventional. The third area is not part&#13;
of traditional concepts of cataloging at all, but will have a major impact&#13;
upon what is available in catalogs in the broadest sense of that term.&#13;
This "non traditional" cataloging involves automated processing of&#13;
documents to extract bibliographic information as well as full text. It&#13;
will expand the range of cataloged objects to include items not generally cataloged due to resource constraints. Automated processing of such&#13;
materials will be characterized by lower quality and less complete&#13;
cataloging, but will nonetheless promote improved access to materials&#13;
that are currently lost to bibliographic control.

Libraries --Automation

Expert systems (Computer science)

Artificial intelligence

Library science --Data processing

</description>
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