expert systems dudychr go ovefivff[1].pptx

Khushi rohilla
Expert systems in libraries
KHUSHI ROHILLA
M-22

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CONTENTS
1. Introduction
2. Definitions of expert systems
3. Characteristics of expert systems
4. Need for expert systems
5. Components of expert systems
6. Application in libraries
7. Features of expert system
8. Limitations of expert systems
9. Conclusion
10. References

INTRODUCTION
Expert system a branch of artificial intelligence is one of the new waves of technology that have
influenced the services of the library. The concept of expert system developed from the subject
domain of artificial intelligence (AI) requires a departure from conventional practices and
programming techniques.
“Expert systems in libraries are computer-based systems that mimic the decision-making abilities of
a human expert in a specific domain, using a knowledge base and inference engine to provide
expert-level advice, support, and solutions to library users and staff, with the goal of improving the
quality, accuracy, and efficiency of library services and operations”. It stores and interprets the
experience and knowledge of human expert by using computer technology. Edward Albert
Feigenbaum has defined an expert system as “an intelligent computer programmes that uses
knowledge and inference procedure to solve problems that are difficult enough to require significant
human expertise for their solutions”
In simpler terms:
"Expert systems in libraries are computer programs that think like a librarian, providing expert
advice and answers to users and staff, making library services more accurate, efficient, and user-
friendly."

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Cambridge international dictionary of English defines an expert system as a computer
system which asks questions and gives answers that have been thought of by a human
expert.
According to Harrod’s librarians glossary. An expert system is a computer system
which embodies certain decision-making processes relating to a particular subject; such
as system comprises of five parts – a knowledge base, an inference machine, an
explanation program, a knowledge refining program, and a natural language processor.
According to Kashyap(1999),an expert system makes the knowledge of experts
available to others in situations where they require expert knowledge , or support of
knowledge of experts available to others in situations where they require expert
knowledge, or support of knowledgeable people or professionals engaged in
development and application in a well-defined area.
Expert systems are a recent product of artificial intelligence. In simple term, an expert
system stores large amount of data and disseminate it in a systematic way as required
by the users.
Subaveerapandiyan, A. (2023).
Definitions of expert system:

CHARACTERISTICS OF EXPERT SYSTEM:
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 Expert system in Artificial intelligence offers the highest level of expertise. It provides efficient and
accurate solution to imaginative problem.
 An expert system has adequate response time. The total time must be less than the time taken by a
human expert to get the most accurate solution for the same problem. An expert system interacts in
a very reasonable period of time with the user.
 It is always reliable and does not make much mistake.
 Expert system has to link with meta knowledge that means it is known about themselves with own
knowledge limitations and abilities. Due to implementation of meta knowledge, it makes more
interactive and simple for several data representations.
 Capable of handling challenging decisions and problems: An expert system is capable of handling
challenging decision, problems and delivering solution.

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NEED FOR EXPERT SYSTEM:
 Expert systems can answer questions and solve problems much faster than the human expert.
 Due to the capabilities of computers of processing a huge number of complex operations in a
guide & accurate way, expert systems can provide both fast and reliable answers in situation
where the human experts cannot.
 Expert system can be used to perform monotonous operations and other that are boring or
uncomfortable to humans.
 Substantial savings can be achieved from using expert system.
 Human get tired from physical or mental workload, expert system cannot.
 Human have limited working memory and unable to process complex, large amount data.
• Humans lie, hide and die. He may also retire or transferred from his job while the expert system is
also
available.
• Expert system does not forget or never make mistake in calculation.
Murthy, S. S. (2017).

COMPONENTS OF EXPERT SYSTEM
User interface Interference engine Knowledge base
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User interface is the component which enables the user to communicate with
the expert system. Most expert systems are interactive; they need users to
input information about a particular situation before they can offer advice.
Most of the existing user interfaces of expert systems are menu driven,
accepting single words or short phrases from the human user. A few have
natural language capabilities.
The expert system aims to assist or advise the non-expert users, but it will be
consulted only if it helps the users to perform that task more easily. Thus,
expert systems must meet all the requirements of good interface design.
(e-gyankosh,n.d.)
User interface:

INTERFERENCE ENGINE:
interference engine stands between the user and the knowledge base. It performs two
major tasks:
first, it examines existing facts and rules, and adds new facts when possible;
second, it decides the order in which inferences are made.
In doing so, the inference engine conducts the conclusion with the user.
The inference strategies used in expert systems are:
 Modusponens
 Reasoning about uncertainty
 Resolution
Engine part of the system means it is used to drive around amongst the various inferences it
might make. This means it allows to pursue reasoning strategies or control strategies as they
are sometimes called, to decide what operators to apply at each stage of the search.

The most common control strategies used in expert systems are forward
chaining, backward chaining and bi-directional. Broadly speaking, forward
chaining involves reasoning from data to hypotheses, while backward
chaining attempts to find data to prove, or disapprove, a hypothesis. Pure
forward chaining leads to unfocused questioning in a dialogue mode system,
whereas pure backward chaining tends to be rather relentless in its goal-
directed questioning. Most successful expert systems use bi-directional
reasoning method.
Asemi, A., Ko, A. And nowkarizi, M. (2021),
Interference engine (contd…1)

KNOWLEDGE BASE:
The knowledge base is a vital component of an expert system. It
embodies the expert knowledge the system needs to do the tasks it is
designed to carry out during its everyday processing.
Different types of knowledge may need to be incorporated:
oKnowledge about the problem domain.
oKnowledge about objects in the problem domain.
oFacts specific to the problem domain.
oThe factual information held by the system is data about the domain
which
do not vary whatever particular circumstances are considered.
(Asemi, A., Ko, A. and Nowkarizi, M. (2021),)

KNOWLEDGE BASE (CONTD..1)
These data are stored in a conventional data base. During system
processing, data specific to the set of conditions being considered at a
particular time are held in the 'working memory' and are usually discarded
at the end of the session Of more interest is the human expert knowledge
which relates to the problem domain or to the objects of the domain. This
knowledge cannot be stored in a conventional data base, but it has to be
represented by a formalism that is suitable for the kind of manipulation
required by the tasks that the system is performing.
(Asemi, A., Ko, A. and Nowkarizi, M. (2021)

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COMPONENTS OF EXPERT SYSTEM (CONTD…)

Application in Libraries
Application
of expert
systems in
libraries
Staff
management
Administratio
n
Collection
development
classification Cataloging
Reference
services
Planning
Technical
services
14

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Application in Libraries (contd..1)
Administration:- Library administration must deal with complex problems on a day-to-day basis.
Problems with budgeting, staff, and planning are just a few of the difficulties they face every day.
During budget cuts, the administrator must determine what items to cut and by how much. Should
staff be reduced? Should serials be cancelled? Will there be any money to buy books or equipment?
An expert system could be helpful in assisting the administrator in making these decisions. One
could develop a system composed of the heuristics (rules-of-thumb) that librarians use to make
these decisions.
Staff management:- Staff management in hiring, promoting and placement of the staff, an expert
system might be useful. By using criteria such as qualifications required for the job and
experience, an expert system could be used to assist in the hiring process. An expert system could
be developed to determine which staff members should receive raises, disciplined, or dismissal.
Planning:- An expert system using information from patterns and material usage could help plan
for remodeling or new facilities. The system would help the administrator to determine where the
circulation desk should be located, where the copy machine should be placed, and where the OPAC
terminals would get the most use.
GLADNESS, K. (2023).

Application in Libraries (contd..2)
• Technical Services:- More efforts have been in developing expert system applications for technical services. The focus
of research efforts are witnessed in the areas of cataloguing, collection development.
• Cataloguing :- Expert systems have been developed to create MARC record6 and to apply some of the rules in AACR-
2 for cataloguing. Roy chang7 developed a cataloguing expert system based on the rules in AACR-2. He determined
that its usefulness was limited because the system had no means of interpreting the rules. In this opinion 'cataloguing
problems today are too widespread For employing an expert system’.
• Classification:- Classification is also a difficult area for an expert system. While there are guides to determine
classification numbers and subject headings, there are no strict rules available, and the relationship between objects
and classes are often ambiguous. Research is progressing in the development of systems for assigning subject headings
and class numbers.
• Collection Development:- There are only two possible responses when one considers new materials for acquisition or old
materials for discarding; yes or no. With only two possible responses, it is easier to develop an $expert system. There
has been at least one successful attempt at building expert system for collection development at Applied Physics
library.
• Reference Service:- Expert systems would be useful for assisting patrons in locating materials and information. Expert
systems may prompt the user for the type of information needed and display materials that may contain it.
Gladness, K. (2023).

Features of Expert system:
(1.) Experts can be freed from routine tasks and made available for more exciting, creative
and demanding work.
(2.) Expertise can be pooled when more than one expert contributes to the system
development. The pooling exercise can assist in the refinement of the procedures and help
to make them more consistent.
(3.) Knowledge can be safeguarded, developed and distributed. Enormous sums of money
are spent on training individuals, yet all their knowledge and expertise is lost when they
die or leave the company. Expert systems offer a way of capturing this expertise and
knowledge and at the same time making it available to other people.
(4.) Expertise can be available. Since expert systems provide explanations for advice given
they can be used 24 hours a day without the presence of the expert.
(5.)Expert systems can be used for training purposes. The- problem-solving and
explanation capabilities of expert systems are particularly useful in training. Situations.
Training can also be distributed throughout a company and done on an individual basis at
times suited to the employee.

Features of Expert system (CONTD...1)
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(6.) Expert systems can provide a standardized approach to problem solving.
(7.) The development of an expert system offers the expert with an opportunity to critically assess
and improve his problem-solving behavior.
(8.) The performance of non-experts can be improved over a period of time and they may
eventually even reach expert status.
(9.) In many situations, expert systems can provide solutions to problems far more quickly than a
human expert.
(10.) Expert systems have the potential for saving companies a vast amount of money, thus
increasing profits.

The expert systems are often created utilizing the software development
Methodology called prototyping. The objective of the software prototype is
to validate proposed designs by constructing a low-cost system that has
enough functionality to test out major designs decisions. The prototyping
allows developer to fairly quickly create one or more systems that
approximate the final system. However, there is no any guarantee that
software techniques utilized in the small-scale prototype will work in the
large-scale production system. This can lead to a false sense of
accomplishments. In most libraries, expert systems are prototypes, not
production systems.
( MURTHY, S. S. (2017).
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Limitations of expert system:

LIMITATIONS OF EXPERT SYSTEM (CONTD…1)
It is evident that no technology is entirely perfect to offer easy and complete
solution. Also, the level and caliber of effort that must be expended to create
an expert system is directly related to the power and complexity of that
system. The more intelligent the system is the greater the effort that must
be expended to create it and also the greater the degree of expertise that is
needed to do so. Larger systems are not only expensive but also require a
significant amount of development time and computer resources. There is
also the need for skilled personnel combined with expensive developed
tools.
(MURTHY, S. S. (2017).
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CONCLUSION
The usefulness of expert systems in library and information systems will depend on
increasing power and efficiency of hardware and software. To be able to offer expert
system services to their clients, libraries will have to be involved in the following areas:
A. Development of prototype 'systems.
B. Development of knowledge representation schemes.
C. Experimentation with knowledge-based indexing, abstracting, and classification.
D. Experimentation with specialized development environments for specific domains
of knowledge.
As knowledge based expert systems become more acceptable in the library community,
libraries will begin to develop, purchase and maintain interactive knowledge-based
expert systems for their clients.

REFERENCES
 Subaveerapandiyan, A. (2023). Application of Artificial Intelligence (AI) In Libraries and Its Impact on Library
Operations Review. Library Philosophy and Practice, , 1-19.
 Gladness, K. (2023). Constraints Facing African Academic Libraries in Applying Electronic Security Systems to
Protect Library Materials. International Journal of Librarianship, 8(1), 31-48.
 https://egyankosh.ac.in/bitstream/123456789/10553/1/Unit-1.pdf
 Asemi, A., Ko, A. and Nowkarizi, M. (2021), "Intelligent libraries: a review on expert systems, artificial
intelligence, and robot", Library Hi Tech, Vol. 39 No. 2, pp. 412-434. https://doi.org/10.1108/LHT-
02-2020-0038
 Murthy, S. S. (2017). Expert systems for library and information services. DESIDOC Bulletin of Information
Technology

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