International Journal of Innovation and Research in Educational Sciences Volume 5, Issue 4, ISSN (Online) : 2349–5219

Artificial Intelligence and Expert System: Intelligent Library

DR. SHIVA SHRIVASTAVA LIBRARIAN Truba Institute of Engg. & Info. Tech., Bhopal ; Email ID : Date of publication (dd/mm/yyyy): 31/08/2018 Abstract – As we all know about the development of latest AI will come bundled with OPAC’s, online services and technology in every field, and the library science is not communications networks. It is commercial knowledge exception of it. This paper explores many things regarding based industry rather than local development efforts. impact of Artificial intelligence and Expert Systems on library Through the application of artificial intelligence field, type of artificial intelligence in libraries and how technologies numerous prototype intelligent library artificial intelligence as a expert system actually works for libraries. Artificial Intelligence (AI) is concerned with systems have been created for the library routine work like intelligent behavior in artifact and intelligent behavior, in cataloging, indexing, information retrieval, Reference and turn, involves perception, reasoning, and learning, other purposes. To build an intelligent computer system we communicating, and acting in complex environments. need to collate, organize, represent and use human expert An expert system is a subset of AI which is a subfield of knowledge in a narrow vertical domain computer science concerned with designing systems that An expert system is a computer program that attempts to perform human-like intelligent function. In order to meet the mimic human experts by the system's capability to render requirements of a genuine expert system, the intelligent advice, to teach and execute intelligent tasks. capabilities of humans must be rivaled essence, the human Library developed expert systems will address problems thinking public reasoning processes are cloned. For e.g., the expert system must ask intelligent questions, solve problems, in a number of areas. Most will focus on narrow domains explain reasoning, and justify conclusions. An expert system is with an emphasis on local concern. Information and referral basically an intelligent computer program that uses and system s will be among the first expert systems to be inference procedures to solve problems that are difficult developed by libraries. Expert system will assume an enough to require significant human expertise for their important role in library instruction and clearing houses will solutions. allow libraries to share tutorial systems with one another. Tutorial systems may one day replace library work books Keywords – Artificial Intelligence (AI), Expert System (ES) and other forms of in house documentation for user Knowledge, Latest Technology, Intelligent Library. assistance. The future of expert systems in libraries will follow the evolution of expert systems as knowledge I. INTRODUCTION media. Expert systems, which are now clever, occasionally Artificial Intelligence and Expert System useful computer programs, will eventually assume and Artificial Intelligence (AI) is the science and technology important role as a format for recording the working that seeks to create intelligent computational systems. knowledge of human experts. Information media vary in Researchers in AI use advanced techniques in computer suitability for carrying different types of message, and science, logic and mathematics. It helps in to build expert system are now exception. One of the major uses of computers and robots that can mimic or duplicate the expert systems will be to reconcile the differences among intelligent behavior found in humans and other thinking other information media, but the following two basic things. The desire to construct thinking artifacts is very old problems are likely to remain: and is reflected in myths and legends as well as in the 1. Knowledge is growing exponentially. The classic creation of lifelike art and clockwork automatons during the information explosion is being compound in by the Renaissance. AI as we know it today’s is relatively new introducing of new computer-based media, and the field. Even though some ground work had been laid earlier, merging of exiting media. Not only will there be merge AI began in earnest with the emergency of the modern more recorded knowledge, there will be new formats computer during the 1940’s and 1950’s. It was the ability of and forum for storing and communicating knowledge. these new electronic machines to store large amounts of 2. Knowledge is heterogeneous. There is no search thing information and process it at very high speeds that gave as a uniform structure for representing knowledge. researchers the vision of building systems which could Knowledge is not data. It is fusion, abstract, and bound emulate some human abilities. AI requires an up with language, and consequently any thesauri, understanding of related terms such as intelligence, classification, schemes, record structures are formalisms knowledge, reasoning, thought, cognition, learning and a for representing knowledge are limited. number of computer related terms. AI encompasses the Intelligent Library following general areas of research: (1) automatic An intelligent library have the ability to personalize, programming, (2) computer vision, (3) expert systems, (4) maximum-reuse, index, analyze and integrate valuable intelligent computer-assisted instruction, (5) natural information and knowledge from a wide selection of language processing, (6) planning and decision support, (7) existing sources. A number of tightly integrated search robotics, and (8) speech recognition. components (text search, audio search and video search) can be used. Such search possibilities ensure that take Copyright © 2018 IJIRES, All right reserved 476 International Journal of Innovation and Research in Educational Sciences Volume 5, Issue 4, ISSN (Online) : 2349–5219 advantage of quickly retrieving the most relevant -igence techniques in library automation systems. information from the available content that has already been The Intelligent systems are often created utilizing the developed and approved for different manuals, handbooks, software development methodology called prototyping: directives, research, normative documents, databases of The objective of the software prototyping is to validate best practice and other sources. Although an intelligent proposed designs by constructing a low-cost system that has library can allow users to type queries in all languages, enough functionality to test out major designs decisions on word meaning, words frequency and combination when the examples. The Prototyping allows developers to fairly developed search engine’s only purpose is to retrieve quickly create one or more systems that approximate the documents or their parts based on a keyword search. final system however, there is no any guarantee that the Promising AI tools and Techniques and the Major software techniques utilized in the small-scale prototype Components of ES are will work in the larger-scale production system. This can The breadth and diversity of AI there are a number of lead to a false sense of accomplishments. In the many technological tools and techniques that may be valuable in library expert systems are prototypes, not production constructing intelligent library systems. Some, such as systems. neural networks, are too immature to assess their The level and caliber of effort that must be expended to usefulness. The following list briefly summarizes selected create an intelligent system is directly related to the power AI tools and techniques. It is by no means a comprehensive and complexity of that system. The more “intelligent” the list of potentially useful tools and techniques. system is, the greater the effort that must be expended to  Knowledge base :- The software that represents the create it and the greater the degree of expertise that is knowledge. needed to do so. The need for skilled personnel combined  Inference engine :- The reasoning mechanism. with expensive development tools (e.g., advanced expert  User interface :- The hardware and software that system shells) or techniques (e.g., original programming in provide the dialogue between people and the logic or procedural languages) makes the creation of Computer. sophisticated intelligent systems a potentially costly venture.  Domain expert :- The individual who is considered an expert.  Knowledge is not always readily available.  Knowledge engineer :- The individual who acquires  It can be difficult to extract expertise from humans. and represents the knowledge.  There are frequently multiple correct assessments.  Explanation facility :- The software that answers  Time pressures. questions such as "Why" and “How."  Users have cognitive limits.  Blackboard :- A workplace for storing and working on  ES works well only within a narrow domain of intermediate information. knowledge.  Reasoning improvement :- A facility (not available  Most experts do not have an independent means to commercially) for improving the Reasoning validate results. capabilities of an ES.  Vocabulary is often limited and difficult to understand.  User :- The non-expert who uses the machine for  Help from knowledge engineers is difficult to obtain consultation. and costly.  Hardware :- The hardware that is needed to support  Potential for lack of trust on the part of the end-users. the ES.  Knowledge transfer is subject to biases. Genetic Categories of ES Applications are: Targeted Development Efforts and success features of Rule-based ES: Knowledge is represented by a series of ES rules. AI is a means to an end any tool, it has strengths and Frame-based systems: Knowledge is represented as a limitations. Our true goal is not to create systems based on series of frames (an object-oriented approach). AI technologies is to create most the powerful, flexible, and Hybrid systems: Involve several approaches such as easy to use systems possible for ourselves and our patrons. fuzzy logic and neural networks. AI is one tool in the toolbox which should be employed Model-based systems: Structured around a model that when the characteristics of the task at hand indicate that an simulates the structure and function of the System under AI solution that is called for. And the success features of ES study. are: Ready-made systems: Utilize prepackaged software.  Level of knowledge must be sufficiently high. Real-time systems: Systems designed to produce a just-  Expertise must be available from at least one expert. in-time response.  The problem to be solved must by fuzzy. Strategies for Future progress in Library and  The problem must be narrow in scope. Limitations of ES are  The shell must be of high quality and naturally store By recognizing the limitations of contemporary artificial and manipulate the knowledge. intelligence techniques that’s why establish realistic goals  The user interface must be friendly to novice users. for intelligent library systems and devise appropriate  The problem to be solved must be difficult and system develop strategies. This section discusses some important enough to justify the development of a promising approaches to the application of artificial intell- system. Copyright © 2018 IJIRES, All right reserved 477 International Journal of Innovation and Research in Educational Sciences Volume 5, Issue 4, ISSN (Online) : 2349–5219

 Knowledgeable developers with good people skills are -apolis: Howard W. Sams& Company, 1988. [4] Joseph M.A. Cavanagh,“Library Applications of Knowledge- needed. Based Systems,” The Reference Librarian no. 23, 1989, pp.1-19.  The impact of the ES must be considered. [5] Linda tag">C. Smith, “Artificial Intelligence and Information  The impact should be favorable. Retrieval,” Annual Review of Information Science and  Management support is needed. Technology 22, 1987, pp. 41-77. [6] Louis E. Frenzel, Jr., Crash Course in Artificial Intelligence and Abbreviations Expert Systems (Indianapolis: Howard W. Sams & Co., 1987 AI: artificial Intelligence [7] P. F. Anderson,“Expert Systems, Expertise, and the Library and ES: expert system Information Professions,” Library and Information Science Research 10, October 1988, pp. 367-388. [8] Rao Aluri and Donald E. Riggs, “Application of Expert Systems II. CONCLUSION to Libraries,” Advances in Library Automation and Networking 2,1988, pp. 1-43. Different reports contained an explicit criticism of the [9] Tim Holthoff, “Expert Librarian Applications of Expert Systems to Library Technical Services,” Technical Services Quarterly 7, libraries focus on their specific collections and a no. 1,989, pp. 1-16. recommendation to focus more on user needs. There is a [10] Townley, C.T. (2001). Knowledge Management and Academic need to overpass the key limitations in the development of Libraries. College & Research Libraries, 62(1),pp.44–55. traditional libraries, which have been developed for a particular content and a specific group of learners. We suppose that the future libraries will become a practical knowledge storehouse and will offer intelligent opportunities for people. Through the application of artificial intelligence technologies numerous prototype intelligent library systems have been created for the library routine work like cataloging, indexing, information retrieval, reference, and other purposes. However the relatively few of these systems have evolved into production systems that are used in the daily operations of libraries. AI research has been underway for more than 2 decades it is only in the past 2 years that AI’s impact has been measurable. To some degree the lack of penetration of AI technologies in libraries is due to the fact that appropriate tools and techniques have only been widely available for the relatively short time. Though there were other theoretical, technological, fiscal and human resource barriers as well and these significant problems are ongoing. This paper has outlined some of the major limitations of AI technologies of particular interest to libraries and suggested some possible. Strategies for making progress in building artificial intelligent library systems. AI offers us a powerful set of tools, especially when they are combined with conventional and other innovative computing tools. It will not be an easy task to master those tools and employ them skillfully to build truly significant intelligent library systems. The use of intelligent Library systems is unlikely to be widespread until we move from the current era of hand-crafted intelligent systems to a future era of turnkey intelligent systems. To accomplish goal vendors and a small number of progressive libraries will need to create powerful, transportable and marketable intelligent library systems based on the continuing advances made in the commercial AI marketplace.

REFERENCES

[1] Chen, L. S.” Design and implementation of intelligent library system. Library Collections Acquisitions & Technical Services”, 32(3-4), 2008, pp.127–141. [2] George F. Luger and William A. Stubblefield, Artificial Intelligence and the Design of Expert Systems (Redwood City, CA: Benjamin/Cummings Publishing Co., 1989. [3] Henry C. Mishkoff (revised by Dan Shafer and Daniel W. Rasmus), Understanding Artificial Intelligence, 2nd ed. (Indian- Copyright © 2018 IJIRES, All right reserved 478