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Data Mining: a Library Utility Model

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Data Mining: a Library Utility Model European Journal of Research www.journalofresearch.de ¹ 1/2019 [email protected] SOCIAL SCIENCE AND HUMANITIES Manuscript info: Received December 12, 2018., Accepted December 17, 2018., Published January 20, 2019. DATA MINING: A LIBRARY UTILITY MODEL Pardeep Rattan Librarian Government College, Phase VI, SahibzadaAjit Singh Nagar (Mohali)- Punjab [email protected] http://dx.doi.org/10.26739/2521-3253-2019-1-4 Abstract: Documents, Users, Services, Finances, Human resources and Space are to library, what library is to an institution. Library perhaps is the only service agency that through its robust and helpful library system, based on tools and techniques of information and communication technology is able to satisfy the information needs of a user across the globe 24x7x365 that comes out to be 61320 hours in an year.Libraries through Data mining (DM)techniques would be able to strengthen its managerial and decision support system where data is analysed from different perspectives which in turn would provide an edge to an organisation like library to serve their clients in a better way. An attempt has been made through this conceptual paper to identify the core library areas where data mining techniques can be applied to build a stronger serviceable library system for the maximum benefit of library users. Keywords: Data Mining, ICT, Electronic Libraries, Data Knowledge Discovery, Data Warehousing. Recommended citation: Pardeep Rattan. DATA MINING: A LIBRARY UTILITY MODEL. 1 European Journal of Research P. 39-45 (2019). INTRODUCTION Information communication technology tools and techniques have influenced and transformed all the human activities across the globe and have forced the social, economic, education, health, agriculture, weather, scientific and research organizations world over to think, devise, implement and serve the humanity in the most befitting way by implementing them. The indelible impact and benefits of ICT in libraries and information centres has in fact made the availability of filtered, accurate, tailored and timely information to the users in digital form via World Wide Web, Internet and in-house databases. Information of any kind and in any format is vital to the growth, development and expansion of all parameters of human life. The selection of information sources and their format in any library is the Vienna, Austria Generalization of Scientific Results 39 European Journal of Research www.journalofresearch.de ¹ 1/2019 [email protected] direct outcome of clear cut well defined policy - the collection development policy which is formulated by keeping in mind the aim, mission, vision and target audience of the parent institution. Data mining helps in the management of data from the reports generated from different sections of the library that would lay a base for collectiondevelopment, budgetary provisions, usage of resources, thrust areas, weaknesses, clientele interest, timings, human resources where the library has to work upon to continue or to modify the set structure to strengthen the current library system. It would also help the library governing body for a long term and sustained library development programme. DATA AND INFORMATION Data and information are the terms used interchangeably in routine practices. However, the thin line between these two terms is identifiable by the information specialists and the managers who manage the data to convert it into information for the end user through processing using IT techniques in today's electronic age. Data are recorded facts, events, and transactions and so on. They act as input material from which information as per need is generated based on the data. In other words information is analyzed data useful for the user. In clearer terms and to be more specific, Edward and Finlay has put it " without an efficient means of filtering and aggregating data a manager could be... data rich yet information poor." The characteristics of time, accuracy, relevance, completeness, understanding and verification make information complete information. A complete information system helps in decision making by virtue of its nature of clarity, uncertainty and monitoring and control. Computer Based Library Information System (CBLIS) use electronic aids, tools and technology to generate relevant information which can be understood from following figure:- It has been said that recipe for a good decision is "90 percent information and 10 percent inspiration."Information acts as a catalyst for the managerial functions of planning, operating and controlling. Vienna, Austria Generalization of Scientific Results 40 European Journal of Research www.journalofresearch.de ¹ 1/2019 [email protected] Norbert Wiener has put it like this," any organism is held together by the possession of means for the acquisition, use, retention and transmission of information." DATA MINING (DM) and LIBRARIES Data Mining (DM) is a computational process which helps to discover different patterns among large data through artificial intelligence (knowledge discovery) and machine learning, statistics (data analysis) and database systems. It is also called Data Knowledge Discovery (DKD) where data is analyzed to derive meaningful and useful information from different perspectives as per requirement, future planning and to seek present trends of the parent organization.It may be used in libraries to find useful but undiscovered pattern in a large collected data. It identifies the hidden patterns or distinct characters which otherwise were unknown or hidden that may be helpful for making decisions. Online dictionary of library and information science (ODLIS) defines data mining as "the process of using database applications to identify previously undetected patterns and relationships within an existing set of data." More and more organisations today are depending on data mining analysis for making targeted business decisions because of the following Capabilities of DM:- ^ The required extensive manual workouts on of data analysis are moderated to a greater extent into automated prediction of trendsand behaviours which helps in targeted marketing, future trends prediction and in identification of a particular set of clients using a particular service and product. ^ The different tools employed in DM through automated discovery of previously unknown designs or normsor trendshelp to identify the hidden patterns. It can be best understood by an example where in a library scenario a particular group of library users ask for a specific information resource or a subject specific consultation. In a report for the University Libraries at Virginia Tech., Young & others (2017) advocated that academic librarians should playpro active role as facilitators of text and data mining (TDM) to identify and review the research trends and to study the undetected data relationships. The academic libraries have traditionally been a source for peer reviewed research and other scholarly literature. Prakash, Prem Chand and Goyal in a study on Application of DM in Library and Information Science have strongly put a case in favour of DM for libraries for better decision making by connecting segregated sources of data which many libraries in their day to day operations. Uppal and Chindwani (2013) suggested that through DM techniques related books on the same stream can be suggested to readers for further Vienna, Austria Generalization of Scientific Results 41 European Journal of Research www.journalofresearch.de ¹ 1/2019 [email protected] reading, the arrangement of books and other documents can be altered based on frequent sequences of search and circulation and the readers interest can be gauzed by association rule of DM. Chen (2013) in a conference paper on study of DM in digital libraries put forward a model of DM for digital libraries. He advocated that DM helps to optimise automatic information processing, improves information quality and business with reduced costs and provides a direction for strengthening digital library collection. Carnegie Mellon University and Georgetown University through text and data mining on a digital humanities project have recreated the British Early Modern Social network to trace the personal relationships among popular personalities form literature and science like Bacon, Shakespeare, Isaac Newton and many more. Some of the projects at the University also analyses the visual data along with the textual data. In her study on the "Application of Data mining Technology in Digital Library" Zhang (2011)had taken up a case study of "low utilization readers" at Linyi University Library in which according to the nature of behaviour of readers of high and low borrowing rate the data was mined and analyzed to establish factors for their low borrowing. It could provide help in decision making for library to manage and develop appropriate strategies to attract readers and also to predict reader use in the strategy. The author was of the view that DM technology in libraries would usher into a new realm for faster development of librarianship and create good social benefits. Prediction Behavioural patterns of future within data Identification Current norms, activities, items, focus Classification Categorisation of data into different sets based on different parameters Optimisation Extent of finances, time, space, materials etc. For optimisation of output within limitations of an organisation GOALS OF DATA MINING The following graphic representationhelps to understand the process
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