A. R. D. Prasad ¹, Pijushkanti Panigrahi ²

Affiliations
1 Documentation Research and Training Centre, Indian Statistical Institute, R V College, P O Bangalore, PIN - 560 059, IN
2 Dept of Library and Information Science, University of Calcutta, 3rd FloorAsutosh Building, 87/1 College Street, Kolkata, PIN - 700 073, West Bengal, IN

Abstract

Elaborately discusses the treatment of the time isolates of Colon Classification (CC), 7th edition in the automatic environment. From the very beginning CC has separately specified isolate numbers for time, which is one of the five fundamental categories. As the time isolates can appear with any one of the Main Classes enlisted in the schedule of basic subjects, the schedule for time isolates is mentioned as a common schedule. This research paper describes the importance of time (i.e. Meteorological time, Civil time, etc.) in classifying the thought content of any document. It also discusses the structure of the schedule of the Common Time Isolates including all divisions and subdivisions. Discusses the rules of expert systems developed using Prolog to handle the procedure of picking up numbers from other schedules and forming the special components to build compound time isolates. Describes the procedure of developing knowledge base in respect of time isolates. Some special techniques of defining lexical knowledge regarding time isolates are also discussed. Working procedure of different program segment of inference engine is illustrated. Includes the scope of forming compound time isolates according to CC7. Illustrates the specific techniques used for different groups to follow the instruction of the schedule.

Keywords

Automatic Classification, Analytico-Synthetic Classification, Colon Classification, Artificial Intelligence, Time Isolates.

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Pijushkanti Panigrahi ¹, A. R. D. Prasad ²

Affiliations
1 Dept of Library and Information Science, University of Calcutta, 3rd FloorAsutosh Building, 87/1 College Street, Kolkata 700 073, West Bengal, IN
2 Documentation Research and Training Centre, Indian Statistical Institute, R V College P O, Bangalore 560 059, IN

Abstract

Colon Classification designed by Dr S R Ranganathan has gained popularity due to its analytico synthetic nature. From the very beginning it has separately specified isolate numbers for Space or Geographical areas, which is one of the five fundamental categories. As the space isolates can occur in any one of the Main Classes enlisted in the schedule of basic subjects, the schedule for space isolates is mentioned as a common schedule. This research paper describes the importance of space / geographic area in classifying the thought content of any document. It also discusses the structure of the schedule of the Common Space Isolates including the political divisions and subdivisions of continents and subcontinents and the administrative divisions of the country. Indicates the possibilities of using mother country and favoured country. Mentions the procedure of developing the knowledge base for divisions and subdivisions of geographical areas. States the rules of expert systems developed using Prolog to handle the procedure of picking up numbers from other schedules and forming the special components to build compound space isolates. Applies the frame based knowledge representation technique to develop knowledge base for different groups of isolate ideas as derived in CC7 using characteristics like 'by geographical feature', 'by population cluster', 'by zone', 'by area surrounded by ocean', 'by orientation', 'by empire' etc. Illustrates the specific techniques used for different groups to follow the instruction of the schedule.

Keywords

Automatic Classification, Analytico Synthetic Classification, Colon Classification, Artificial Intelligence, Natural Language Processing, Viswamitra, Space Isolates.

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Renu Seth ¹, A. R. D. Prasad ², Devika P. Madalli ³

Affiliations
1 Max Mueller Bhavan, New Delhi, IN
2 Documentation Research and Training Center, Indian StatisticalInstitute, Mysore Road, 8th Mile, Bangalore 560 059, IN
3 Documentation Research and Training Center, Indian Statistical Institute, MysoreRoad, 8th Mile, Bangalore 560 059, Bangalore, IN

Abstract

In the traditional library environment Cataloging in Publication (CIP) is very popular and the library staff can make use of CIP records to generate minimal cataloguing information. With the advent of Internet and the presence of book industry on the Net, the growing importance of metadata has resulted in ONIX (ONline Information eXchange). The benefits of crosswalk between ONIX and Dublin Core are too obvious to be ignored, as it saves the time of cataloguers in generating metadata in Dublin Core for the e-books or even printed books acquired by a library. This paper attempts to investigate the possibility of generating required metadata from available metadata formats, particularly the most popular Dublin Core (DC) from ONIX and presents mapping between ONIX and Qualified Dublin Core.

Keywords

Cataloguing in Publication (CIP), Metadata, Online Information Exchange, Onix, Dublin Core, Qualified Dublin Core, Mapping.

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Pijuskanti Panigrahi ¹, A. R. D. Prasad ², A. Basu ³

Affiliations
1 Dept of Library and Information Science, Calcutta University, 87/1 College Street, Kolkata 700 073, West Bengal, IN
2 Documentation Research and Training Centre, Indian Statistical Institute, 8th Mile, Mysore Road, R V College P O, Bangalore 560 059, IN
3 Dept of Library and Information Science, Calcutta University, Kolkata 700073, West Bengal, IN

Abstract

Researchers had made numerous attempts to design powerful automatic classification system, but those could not bring any well-accepted results. The main problem was successful automatic analysis of title of documents and finding out subject propositions. Because being a purely mental process, classification demands human intelligence for analysing the title to find out its basic subject and other facets, if any, along with its category and also synthesising those facets according to principles, postulates and canons to construct classification number. In other words, the document title, which is in natural language, is anlysed carefully to pick up relevant words (i.e. subject propositions) and those arc synthesised using classifiers expertise to build the classification number. Emergence of Artificial Intelligence (A I) could bring the solution to this problem. Use of Natural Language Processing (NLP) techniques would help in automatic analysis of titles and an Expert System be developed to work exactly in the same way as a classifier does to build classification numbers being guided by canons, principles and postulates. This paper is based on the research work in this line of thinking. Semantic and syntactic components of an AI based system for automatic classification is described. The methodology of building lexicon, parser based on Definite Clause Grammar, knowledge-base based on frame based and rule based knowledge representation model is given with a brief discussion Oil those knowledge representation modeL Needs of developing inference engine is also discussed with example. Shows the wayan expressive title is analysed to pick up noun phrases.

Keywords

Analytico-Synthetic Classification, Automatic Classification, NLP, Semantics, Syntax-Grammar Rules.

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Madhwacharya B. Mundgod ¹, A. R. D. Prasad ²

Affiliations
1 Institute of Social Studies Trust, Bangalore, 560003, IN
2 Documentation Research and Training Centre, Indian Statistical Institute, Bangalore 560059, IN

Abstract

This paper attempts to develop heuristics which help in building an Expert System for the automatic identification of bibliographic data elements from the title pages of documents. The study emphasizes mainly on the physical layout of the title pages and attempts to identify the pattern of appearence of various bibliographic data elements like title, author, publisher etc.

Keywords

Expert System, Bibliographic Data Elements, Automatic Identification, Title Page, Heuristics.

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A. R. D. Prasad ¹, Bidyut Baran Kar ¹

Affiliations
1 Documentation Research and Training Centre (DRTC), Indian Statistical Institute, 8th Mile, Mysore Road, R. V. College Post, Bangalore 560 059, IN

Abstract

Briefly discusses the role of search languages in Information Retrieval and broadly groups the search languages into four categories. Explains the idea of Definite Clause Grammars and demonstrates how easily parsers for boolean Jogie based search languages can easily be developed. Presents a partial Prolog code of the parser that we used in an object-Oriented bibliographic database management system.

Keywords

Information Retrieval, Search Languages, Parser, Boolean Search Expressions, Prolog, Object-Oriented Programming.

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