Artificial Intelligence and its applications in Libraries
Dr. Shivaranjini S. Mogali
University of Agricultural Science
Krishinagar, Dharwad, Karnataka 580005
In this paper an attempt has been made to trace the different applications of Artificial
Intelligence to the libraries. The various concepts such as expert system, natural language
processing, pattern recognition and robotics and their application to the libraries have
enumerated. The advantages and disadvantages of
Artificial Intelligence have also been
Expert System, Natural Language Processing, Pattern
Recognition and Robotics
The first industrial revolution attempted to create machines that could replace
man’s physical power. Industrialization has transformed the society totally and brought
immediate crises in later development. Infact there are machines that can outperform human
beings over the centuries man’s working ability and thinking process have seen a sea change.
society is becoming increasingly centered on information handling, processing, storage
and dissemination, using microelectronic based technologies, today’s computers can stimulate
many human capabilities such as reading, grasping, calculating, speaking, remembering,
comparing numbers, drawing, making judgments, and even interactive learning. Researchers
are working to expand these capabilities and, therefore the power of computers by developing
hardware and software that can initiate intelligent human behavior. For example, researchers
are working on the systems that have the ability to reason, to learn or accumulate knowledge
to strive for self-improvement, and to stimulate human sensory and mechanical capabilities.
Experts are convinced that it is now only a matter of time; the present generation will
experience the impact and utility of new applications based on artificial intelligence in offices,
factories, libraries and homes. This general area of research is known as ‘Artificial
2. Artificial Intelligence
Artificial Intelligence has come a long way from its early roots, driven by dedicated
The expression “artificial intelligence” was introduced as a ‘digital’ replacement
for the analog ‘cybernetics’. Artificial intelligence began as an experimental field with
pioneers like George Boole (1815-1864), Allen Newell & Herbert Simon, who founded the
first artificial intelligence laboratory (Kumar,2004).
The emergence of a new field called
‘Cybernetics’ which has been coined and founded by Norbert Wisner brought together many
parallels between human beings and machine. Cybernetics is the study of communication
between human being and machine. In general Artificial Intelligence is the subfield of
Computer Science concerned with understanding the nature of intelligence and constructing
computer systems capable of intelligence action (Winston, 1999). It embodies the dual
motives of furthering basic scientific understanding and making computers more sophisticated
in the services of humanity. In other words Artificial Intelligence is the study of mental
faculties through the use of computational models.
Artificial Intelligence mainly focuses on understanding and performing intelligent tasks
such as reasoning, learning new skills and adopting to new situations and problems. Artificial
Intelligence or AI for short is a combination of computer science, psychology, and
philosophy. It is concerned with the concept and methods of symbolic inferences by computer
and the symbolic representation of knowledge to be used in making inferences (Nilson,
1998).The most popular Artificial Intelligence programs are the Expert systems, which are
computer programs that embody human mention of Artificial Intelligence which creates
vision of electro-mechanical devices replacing human beings. Hundreds of rules and facts
make up AI programmes and these programmes process ideas and knowledge, not members,
in several different ways.
3. Areas of Artificial Intelligence
Artificial Intelligence focuses on symbolic, non-algorithmic problem solving methods.
Intelligence relies on ability to manipulate symbols. Artificial Intelligence though is a young
discipline, has transformed the society beyond imagination. The goal of its sub areas i.e expert
system, natural language processing, pattern recognition, and robotics is to simulate human
intelligence with computers.
Some of the recent computational techniques and areas that are
utilized in developing fields of Artificial Intelligence are discussed below;
a) Expert System
Expert System are the knowledge based computerized systems which play a role of
intelligence interface or gateway for providing access to database and to obtain relevant
They range in scale from simple rule-based systems with flat data to very large
scale, integrated developments taking many person, years to develop.
An expert system is a
computer program that provides expert advice, decisions or recommended solutions for a
given situation.(wikipedia/expertsystem,2014) The different components of expert systems
are: Knowledge base, Inference Engine, and User Interface.
b) Natural Language Processing
One of the long standing goals of computer science is to teach computers to
understand the language we speak. The Ultimate generation of computer language is the
Natural language. Artificial Intelligence scientists have succeeded in building Natural
language interface to a large extent using limited vocabulary and syntax.
Processing allows a computer to understand the main linguistic concepts within a question or
solution. Its goal is to design and build computer that analyze, understand and generate
language that human use naturally.(Kumar,2004) The different components of natural
language processing are,
speech synthesis, speech recognition,
approaches, information retrieval and
c) Pattern Recognition
It is the process of establishing a close match between some new stimulus and
previously stored stimulus patterns. This process is being performed continually through the
lives of all living things. Pattern recognition is studied in many fields, including psychology,
ethology, cognitive science and computer science.
Pattern recognition is based on either a
priori knowledge or on statistical information extracted from the patterns. The patterns to be
classified are usually groups of measurements or observations, defining points in an
appropriate multi dimensional space.(Wiki,2014) The components of pattern recognition are;
pre-processing, feature extraction, model selection and training, and
The field robotics is often described as the subfield of AI that is concerned with
perceptual and motor tasks.
Robot is a mechanical device which performs automation tasks,
either according to direct human supervision or a pre-defined program or a set of general
guidelines, using artificial intelligence techniques.(Wikipedia/robotics,2014) The
4. Artificial Intelligence and its applications in Libraries
Computers provide the perfect medium for the experimentation and application of
Artificial Intelligence technology in the present era.
AI has more success at intellectual tasks
such as computer based game playing and theorem proving than perceptual tasks. Sometimes
these computer programs are intended to stimulate human behavior and they are built for
technological applications also such as Computer aided instruction (CAI).In many cases the
main goal is to find any technique that does the task quick in the better way.
4.1 Application of Expert System in Library Activities:
Library activities related to the reading materials, users and staff. The application
of Expert Systems where dialogue between staff and users, users and database appears
quite promising. An Expert System will help the librarian in realizing the need for an
improvement in the productivity. A well programmed Expert System will also improve
i). Applications of Expert Systems in Reference Service:
Reference service is a prime activity of any library and the Expert System will
work as a substitute for a reference librarian. Following are some of the examples of
Expert Systems used for Reference Service.
(a) REFSEARCH: It is a system that supplies patrons, the recommended sources to
lookup for certain question. The system can be used to teach students reference skills or
as a computerized aid for practicing reference librarians and information specialists.
(b)POINTER: It was the early successful working application of computer system in the
area of reference work. It directs the users to the reference sources; It is not a Knowledge
Based System but a computer assisted reference program.
(c) Online Reference Assistance (ORA): This system intended to stimulate the services
of an academic reference Librarian for questions of low and medium level, by using
several technologies: a videotext like database, computer assisted instruction modules,
and knowledge based system.ORA consists of Directional transactions like library
locations, services and polices.
(d)AMSWERMAN: An Knowledge based system to help users for reference questions
on agriculture topics. It uses series of menus to narrow down the subject of the questions
and the type of tool needed. It can function as either a consultation system or as a front
end to external databases and CD-ROM reference tools.
(e)PLEXUS: This is a referral tool used in Public Libraries. It includes knowledge about
the reference process, information retrieval about certain subject areas, reference sources,
and Library users. All the above systems are advisory systems for locating reference
source books and factual data.
ii). Application of Expert System in Cataloguing:
Cataloguing is one of the oldest library crafts. Recent attempts to automate
cataloguing through Expert Systems have focused on descriptive cataloguing because it is
considered rule-based(AACR2).There are two approaches for applying artificial
intelligence techniques to cataloguing
a) A human-machine interface, where the intellect effort is divided between the
intermediary and the support system; and
b) An Expert System with full cataloguing capability linked into electronic publishing
system, so that as a text is generated on-line, it can be passed through knowledge based
systems and cataloguing process is done without any intellectual input from an
intermediary. There have been problem in every attempt to convert AACR2 into the
highly structured rules necessary to run the Expert System.
iii). Application of Expert System in Classification:
Classification is the fundamental activity in the organization of knowledge. For this
reason it is prominent in all systems for organizing knowledge in libraries and
information centers. Application of Expert System in the area of classifications in
libraries includes the following:
(a).Coal SORT: It is a conceptual browser designed to serve either as a search or an
indexing tool. Coal SORT consists primarily of a frame-based semantic network and the
software needed to allow users to display portions of it and to move around in the
conceptual structure. The expert knowledge in the system is embodied almost entirely in
the semantic network. There is no procedural knowledge in the system.
(b) EP-X: The Environmental Pollution Expert(EP-X) has certain things in common with
coal SORT in that both are concentrating on enhancing interface using a Knowledge
Based approach. The knowledge base of EP-X consists of hierarchical frame-based
semantic network of concepts and a set of template that express the patterns called the
pragmatic relationship among concepts. These patterns are referred to as conceptual
(c) BIOSIS: BIOSIS uses a knowledgebase, including a significant amount of procedural
knowledge, to assign documents to categories automatically. It is designed as an indexer
aid. BIOSIS uses the information in the titles of biological documents to assign as many
categories as possible of those that would be assigned by human indexers. The indexing
languages are structured and practical representation of information that can be used to
very good advantage of AI applications.
iv). Application of Expert System in Indexing:
Indexing of periodicals is another area where expert systems are being developed.
Indexing a periodical article involves identification of concepts, to translate these
concepts into verbal descriptions, & selecting and assigning controlled vocabulary terms
that are conceptually equivalent to verbal descriptions. The reason for automating the
intellectual aspects of indexing is to improve the indexing consistency and quality. Based
on the information provided by the information provided by the indexer, the systems can
arrive at appropriate preferred terms automatically to assign relevant subdivisions. The
system can make inferences & based on the inference, it can take appropriate action.’
Med Index’ is the best example of indexing system used in the library Indexing activity.
Very few library users have interacted with knowledge based systems. In general,
users have had very little contact with these systems due to the fact that most of them are
not perfect enough to be used by the everyday library patron.
v). Application of Expert System in Acquisition:
The collection of documents is another integral part of the library. The librarian or the
information officer is key person in this activity. The users of the library have a
significant role to play in building electronic collections and that their help and advice
should be solicited in the process. Several systems have been incorporated. Monograph
Selection Advisor, a pioneering effort in applying this emerging technology in another
area of Library Science i.e. building library collection. Specifically, the task modeled is
the item-by-item decision that a subject bibliographer makes in selecting monographic.
The knowledge base has to be broad enough and the interfacing aspect must be easy
enough for the library to get the desired information from the machine.
4.2 Applications of Natural Language Processing in Library Activities:
When we think of the term NPL, the first thought one might have is of being able to
speak or write in a complete sentence and have a machine process the request and speak.
NPL can be applied to many disciplines. To apply this to the field of Library and
Information science and more specifically to searching database such as online public
access catalogs (OPAC)
Indexing is the basis for document retrieval.“The aim of indexing is to increase
precision, the portion of the retrieved documents that are relevant; and recall, the
proportion of relevant documents that are retrieved”. Key words, which have been
weighted by the indexer as being basic to human thinking on a particular subject, will be
fed into the electronic database in the way that will trigger the citing of an article or book
on the computer screen, when these keywords are strung together in the proper sequence
by the searcher. The main constraint is the variability in the ways a concept can be
expressed. (aaai.org/AITOPICS,2014).This variability is partly a matter of semantics, i.e.,
using the word mobile home vs. trailers. The word trailer has been replaced by the word
mobile home in most parts of the country.
Library patrons may not recognize the ambiguity of their search strategy. The use of
natural language for Dialog database searches would allow the library patrons to search
Dialog database directly, without the assistance of information professional. A patron
using an electronic catalog in a library may prefer to have the catalog understand a
complete sentence like “Find all your sources which contain an mention of natural
language processing for the use of Library and information science.” The human librarian
has the advantage of being trained in search & query as well as natural language and can
act as an intermediary between the machine and the library patron. Some URLs are also
case sensitive. In the future, it may be possible to use natural language to access the
website also. Library patrons must become computer literate to take the advantage of this
4.3 Application of Pattern Recognition in Library Activities:
In this era of the Internet and distributed, multimedia computing, new and
emerging classes of information systems applications have swept into the lives of office
workers and everyday people. New applications ranging from digital libraries,
multimedia systems, geographic information systems, and collaborative computing to
electronic commerce have created tremendous opportunities for information researchers
As the application become more overwhelming, pressing and diverse, several well-
know information retrieval problems have become even more urgent in this network-
centric information age. The most fundamental techniques in IR involves identifying key
features in objects. For example, automatic indexing & natural language processing are
frequently used to automatically extract meaningful words. Texture, color, or shape-
based indexing and segmentation techniques are often used to identify images. For audio
and video applications, voice recognition, speech recognition, and scene segmentation
techniques can be used to identify meaningful description in audio and video stream.
Several classes of techniques have been used for semantic analysis of texts or
multimedia objects. Symbolic machine learning, graph-based clustering and
classification, stastistics-based multivariate analyses, artificial neural networks, and
evolution-based programming are among the popular techniques. In this information age,
we believe these techniques will serve as good alternatives for processing analyzing,&
summarizing large amounts of diverse and rapidly changing multimedia information. The
result from a semantic analysis process could be represented in the form of semantic
networks, decisions, rules, or predicate logic. Spreading activation-based inferencing
methods are often used to traverse various large-scale knowledge
One of the major trends in almost all emerging information systems applications is
the focus on the user-friendly, graphical, &seamless Human-Computer Interactions .The
Web-based browsers for texts, images, and videos have raised user expectation on the
rendering and manipulation of information. Recent advances in the development
languages and platforms such as Java, OpenGL, and VRML and the availability of
advanced graphical workstations at affordable prices have also made information
visualization a promising area for research.
4.4 Applications of Robotics in the Library Activities:
Robot is “An automatically controlled, reprogrammable, multi-purpose
manipulator programmable in three or more axes, which may be either fixed in place or
mobile for use in automation applications.” The robots are on scrambling, rolling, flying,
and climbing. They are figuring out how to get here on their own.
As libraries provide a growing array of digital library services and resources, they
continue to acquire large quantities of printed materials. This combined pressure of
providing electronic and print-based resources and services has led to severe space
constraints for many libraries, especially academic research libraries. The goal of the
Comprehensive Access to Printed Material (CAPM) is to build a robotic, on-demand and
batch scanning system that will allow for real-time browsing of printed material through
a web interface. The user will engage the CAPM system that, in turn, will initiate a robot
that will retrieve the requested item. The robot will deliver this item to another robotic
system that will open the item and turn the pages automatically. By using existing
scanners, optical character recognition (OCR) software, & indexing software developed
by the Digital Knowledge Centre, the CAPM system will not only allow for browsing of
images of text, but also for searching and analyzing of full-text generated from the
5. Advantages of Artificial Intelligence
a) Can take on stressful and complex work that humans may struggle /can not
b) Can complete task faster than a human can most likely;
c) To discover unexplored things. i.e. outer space;
d) Less errors and defects;
e) Function is infinite. (sstramel,2014)
6. Disadvantages of Artificial Intelligence
a) Lacks the "human touch"
b) Has the ability to replace human jobs
c) Can malfunction and do the opposite of what they are programmed to do
d) Can be misused leading to mass scale destruction
e) May corrupt younger generation(sstramel,2014)
The numerous applications of Artificial Intelligence have been deployed, that
demonstrated for the time saving, money to Business sectors, Industrial sectors, Military
sectors, Scientific sectors, Academic and Research organizations. AI applications and
their utilities will be increasing day by day in many IT oriented educational Institutions,
which are contributing AI related recorded information on its AI technology and its
utilities in various areas/subject fields. The success in Expert systems field, Natural
Language Processing field, Pattern Recognition field, Robotics field has precipitated
substantial commercial activity, including the formation of many ventures.
practicability of artificial intelligence in the areas such as cataloguing, classification,
documentation, collection development etc appears to be improving year after year. It is
sure that in the near future artificial intelligence will occupy in all the spheres with the
introduction of competent models with AI techniques. Library and Information Science
will be greatly benefited by the development of the efficient expert system for technical
services as well as Information processing and management.
1. Kumar, P.S.G. (2004) Information Technology: Applications. New Delhi: BRPC. Pp
2. Nil’s, J.Nilson. (1998) Artificial Intelligence. New Delhi: Harcourt , 280-281
3. Patrick Henry Winston. (1999) Artificial Intelligence,
Addison Wesley, New Delhi:
4. www. aaai.Org /AITOPICS,(2014)
6. www.wiki.org/Pattern Recognition (04/11/2014)
8. www.wikipedia.org/Robotics (04/11/2014)