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International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME

TECHNOLOGY (IJCET)

ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 4, Issue 5, September – October (2013), pp. 182-188
© IAEME: www.iaeme.com/ijcet.asp
Journal Impact Factor (2013): 6.1302 (Calculated by GISI)
www.jifactor.com

IJCET
©IAEME

KNOWLEDGE MANAGEMENT: VALUE, TECHNOLOGIES AND ITS
IMPLICATIONS
Shakti Kundu
School of Computer Applications,
IMS Unison University, Dehradun, Uttarakhand, India.

ABSTRACT
With the tremendous growth of web in the recent years, the concept of Knowledge
Management has evolved towards a vision more based on people participation and emergence [14].
This line of evolution is termed as Enterprise 2.0 [14]. However, there is an ongoing debate and
discussions as to whether Enterprise 2.0 is just a fad that does not bring anything new or useful or
whether it is, indeed, the future of knowledge management [15][16]. Knowledge management (KM)
comprises a range of strategies and practices used in an organization to identify, create, represent,
distribute, and enable adoption of insights and experiences. Such insights and experiences comprise
knowledge, either embodied in individuals or embedded in organizations as processes or practices
[2-3]. More recently, other fields have started contributing to KM research; these include information
and media, computer science, public health, and public policy [4]. The aim of this paper is to
highlight the value, technologies and implications of knowledge management.
Keywords: Implications, Knowledge, Management, Technologies, Value.
I.

INTRODUCTION

Knowledge Management is one of the hottest topics today in both the industry and
information research world. In our daily life, we deal with huge amount of data and information.
Data and information is not knowledge until we know how to dig the value out of it. This is the
reason we need knowledge management.
Knowledge Management (KM) refers to a multi-disciplined approach to achieving
organizational objectives by making the best use of knowledge. KM focuses on processes such as
acquiring, creating and sharing knowledge and the cultural and technical foundations that support
them.
182
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME

Knowledge Management may be viewed in terms of:
o
o
o

People: How do you increase the ability of an individual in the organization to influence others
with their knowledge.
Processes: Its approach varies from organization to organization. There is no limit on the number
of processes.
Technology: It needs to be chosen only after all the requirements of a knowledge management
initiative have been established.

Or
o
o
o

Culture: The biggest enabler of successful knowledge driven organizations is the establishment
of a knowledge focused culture.
Structure: The business processes and organizational structures that facilitate knowledge sharing.
Technology: A crucial enabler rather than the solution.

Figure 1: View of Knowledge Management
In the subsequent sections, the remainder of the paper is organized as follows: Section II.
describes the value of knowledge management, Section III. discuss technologies that support
knowledge management, Section IV. refers to the implications of knowledge management and
Section V. concludes the paper.
II.

THE VALUE of KNOWLEDGE MANAGEMENT

Some benefits of KM correlate directly to bottom-line savings, while others are more difficult
to quantify. In today's information driven economy, companies uncover the most opportunities and
ultimately derive the most value from intellectual rather than physical assets. To get the most value
from a company's intellectual assets, KM practitioners maintain that knowledge must be shared and
serve as the foundation for collaboration. Yet better collaboration is not an end in itself; without an
overarching business context, KM is meaningless at best and harmful at worst. Consequently, an
effective KM program should help a company do one or more of the following:
183
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME
•

Foster innovation by encouraging the free flow of ideas.

•

Improve decision making.

•

Improve customer service by streamlining response time.

•

Boost revenues by getting products and services to market faster.

•

Enhance employee retention rates by recognizing the value of employees' knowledge and
rewarding them for it.

•

Streamline operations and reduce costs by eliminating redundant or unnecessary processes.

These are the most prevalent examples. A creative approach to KM can result in improved
efficiency, higher productivity and increased revenues in practically any business function.
III.

TECHNOLOGIES that support KNOWLEDGE MANAGEMENT

These technologies roughly correlate to four main stages of the KM life cycle:
1. Knowledge is acquired or captured using intranets, extranets, groupware, web conferencing, and
document management systems.
2. An organizational memory is formed by refining, organizing and storing knowledge using
structured repositories such as data warehouses.
3. Knowledge is distributed through education, training programs, automated knowledge based
systems, expert networks.
4. Knowledge is applied or leveraged for further learning and innovation via mining of the
organizational memory and the application of expert systems such as decision support systems.
All of these stages are enhanced by effective workflow and project management.

Figure 2: Knowledge Management Technologies

184
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME

IV.

THE IMPLICATIONS of KNOWLEDGE MANAGEMENT

•

Database Users: From business class users to the general public, database users will enjoy a new
level of interaction with the KM system including just-in-time knowledge that delivers precise
relevant information on demand and in context. More complex, smart systems will translate to
optimal usability and less time spent searching for relevant information. For example, data
analysts will enjoy simplified access and more powerful tools for data exploitation. The use of
knowledge bases can reduce customer service costs by providing customers with easy access to
24/7 self service via smart systems that reduce the need to contact customer service or technical
support staff. Database users may even create customized views of knowledge bases that support
their needs.

•

Database Developers: The design and development of knowledge based systems will be
considerably more complex than current database development methods. Developers must
consider the overall technical architecture of the corporation to ensure seamless interoperability.
The use of standardized metadata and methods will also facilitate both intra-corporate and intercorporate interoperability. Making effective physical storage and platform choices will be equally
more complex. Both knowledge base developers and administrators must understand the role of
the knowledge base in the overall KM system.

•

Database Administrators: Database Administrators will evolve into Knowledge Managers. The
knowledge base will store and maintain corporate memory and Knowledge Managers will
become the gatekeepers of corporate knowledge. The lines between technical roles such as Web
Developer, Data Analyst or Systems Administrator will blur as these systems merge into and
overlap with KM systems. DBAs will need to have some knowledge about each of these
disciplines.

•

General Public: Even if they are not interacting directly with a knowledge base, the general
public will benefit from the secondary effects of improved customer service due to faster access
to more accurate information by service providers.

Figure 3: Knowledge Management Implications

185
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME

V.

CONCLUSIONS

While highlighting the concept of knowledge management’s value, technologies and its
implications, it is clear that the goal of knowledge management is connecting people, processes and
technology for the purpose of leveraging corporate knowledge. The database professionals of today
are the Knowledge Managers of the future, and they will play an integral role in making these
connections possible.
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International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
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AUTHORS’ INFORMATION

SHAKTI KUNDU received his MCA from Kurukshetra University Kurukshetra, India in 2006,
MPhil in Computer Science from Chaudhary Devi Lal University, Sirsa, Haryana, India in 2008,
MTech in Computer Science & Engineering from Guru Jambheshwar University of Science &
Technology, Hisar, Haryana, India in 2010. The author current research interests are web mining,
knowledge management and web testing. He is life member of CSI, ISTE, IAENG and AIRCC.

188

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  • 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 4, Issue 5, September – October (2013), pp. 182-188 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET ©IAEME KNOWLEDGE MANAGEMENT: VALUE, TECHNOLOGIES AND ITS IMPLICATIONS Shakti Kundu School of Computer Applications, IMS Unison University, Dehradun, Uttarakhand, India. ABSTRACT With the tremendous growth of web in the recent years, the concept of Knowledge Management has evolved towards a vision more based on people participation and emergence [14]. This line of evolution is termed as Enterprise 2.0 [14]. However, there is an ongoing debate and discussions as to whether Enterprise 2.0 is just a fad that does not bring anything new or useful or whether it is, indeed, the future of knowledge management [15][16]. Knowledge management (KM) comprises a range of strategies and practices used in an organization to identify, create, represent, distribute, and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizations as processes or practices [2-3]. More recently, other fields have started contributing to KM research; these include information and media, computer science, public health, and public policy [4]. The aim of this paper is to highlight the value, technologies and implications of knowledge management. Keywords: Implications, Knowledge, Management, Technologies, Value. I. INTRODUCTION Knowledge Management is one of the hottest topics today in both the industry and information research world. In our daily life, we deal with huge amount of data and information. Data and information is not knowledge until we know how to dig the value out of it. This is the reason we need knowledge management. Knowledge Management (KM) refers to a multi-disciplined approach to achieving organizational objectives by making the best use of knowledge. KM focuses on processes such as acquiring, creating and sharing knowledge and the cultural and technical foundations that support them. 182
  • 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME Knowledge Management may be viewed in terms of: o o o People: How do you increase the ability of an individual in the organization to influence others with their knowledge. Processes: Its approach varies from organization to organization. There is no limit on the number of processes. Technology: It needs to be chosen only after all the requirements of a knowledge management initiative have been established. Or o o o Culture: The biggest enabler of successful knowledge driven organizations is the establishment of a knowledge focused culture. Structure: The business processes and organizational structures that facilitate knowledge sharing. Technology: A crucial enabler rather than the solution. Figure 1: View of Knowledge Management In the subsequent sections, the remainder of the paper is organized as follows: Section II. describes the value of knowledge management, Section III. discuss technologies that support knowledge management, Section IV. refers to the implications of knowledge management and Section V. concludes the paper. II. THE VALUE of KNOWLEDGE MANAGEMENT Some benefits of KM correlate directly to bottom-line savings, while others are more difficult to quantify. In today's information driven economy, companies uncover the most opportunities and ultimately derive the most value from intellectual rather than physical assets. To get the most value from a company's intellectual assets, KM practitioners maintain that knowledge must be shared and serve as the foundation for collaboration. Yet better collaboration is not an end in itself; without an overarching business context, KM is meaningless at best and harmful at worst. Consequently, an effective KM program should help a company do one or more of the following: 183
  • 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME • Foster innovation by encouraging the free flow of ideas. • Improve decision making. • Improve customer service by streamlining response time. • Boost revenues by getting products and services to market faster. • Enhance employee retention rates by recognizing the value of employees' knowledge and rewarding them for it. • Streamline operations and reduce costs by eliminating redundant or unnecessary processes. These are the most prevalent examples. A creative approach to KM can result in improved efficiency, higher productivity and increased revenues in practically any business function. III. TECHNOLOGIES that support KNOWLEDGE MANAGEMENT These technologies roughly correlate to four main stages of the KM life cycle: 1. Knowledge is acquired or captured using intranets, extranets, groupware, web conferencing, and document management systems. 2. An organizational memory is formed by refining, organizing and storing knowledge using structured repositories such as data warehouses. 3. Knowledge is distributed through education, training programs, automated knowledge based systems, expert networks. 4. Knowledge is applied or leveraged for further learning and innovation via mining of the organizational memory and the application of expert systems such as decision support systems. All of these stages are enhanced by effective workflow and project management. Figure 2: Knowledge Management Technologies 184
  • 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME IV. THE IMPLICATIONS of KNOWLEDGE MANAGEMENT • Database Users: From business class users to the general public, database users will enjoy a new level of interaction with the KM system including just-in-time knowledge that delivers precise relevant information on demand and in context. More complex, smart systems will translate to optimal usability and less time spent searching for relevant information. For example, data analysts will enjoy simplified access and more powerful tools for data exploitation. The use of knowledge bases can reduce customer service costs by providing customers with easy access to 24/7 self service via smart systems that reduce the need to contact customer service or technical support staff. Database users may even create customized views of knowledge bases that support their needs. • Database Developers: The design and development of knowledge based systems will be considerably more complex than current database development methods. Developers must consider the overall technical architecture of the corporation to ensure seamless interoperability. The use of standardized metadata and methods will also facilitate both intra-corporate and intercorporate interoperability. Making effective physical storage and platform choices will be equally more complex. Both knowledge base developers and administrators must understand the role of the knowledge base in the overall KM system. • Database Administrators: Database Administrators will evolve into Knowledge Managers. The knowledge base will store and maintain corporate memory and Knowledge Managers will become the gatekeepers of corporate knowledge. The lines between technical roles such as Web Developer, Data Analyst or Systems Administrator will blur as these systems merge into and overlap with KM systems. DBAs will need to have some knowledge about each of these disciplines. • General Public: Even if they are not interacting directly with a knowledge base, the general public will benefit from the secondary effects of improved customer service due to faster access to more accurate information by service providers. Figure 3: Knowledge Management Implications 185
  • 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME V. CONCLUSIONS While highlighting the concept of knowledge management’s value, technologies and its implications, it is clear that the goal of knowledge management is connecting people, processes and technology for the purpose of leveraging corporate knowledge. The database professionals of today are the Knowledge Managers of the future, and they will play an integral role in making these connections possible. REFERENCES [1] "Introduction to Knowledge Management", University of North Carolina at Chapel Hill, Retrieved 18 April 2013. [2] Nonaka, Ikujiro, "The knowledge crea ting company". Harvard Business Review 69 (6): 96– 104, 1991. [3] Nonaka, Ikujiro; Von Krogh, Georg, "Tacit Knowledge and Knowledge Conversion: Controversy and Advancement in Organizational Knowledge Creation Theory", Organization Science 20 (3): 635–652, 2009.doi:10.1287/orsc.1080.0412. [4] Bellinger, Gene, "Mental Model Musings", Systems Thinking Blog, Retrieved 18 April 2013. [5] Addicot, Rachael; McGivern, Gerry; Ferlie, Ewan, "Networks, Organizational Learning and Knowledge Management: NHS Cancer Networks", Public Money & Management 26 (2): 87– 94, 2006. doi:10.1111/j.1467-9302.2006.00506.x. [6] Gupta, Jatinder; Sharma, Sushil, “Creating Knowledge Based Organizations”, Boston: Idea Group Publishing, 2004. ISBN 1-59140-163-1. [7] Maier, R., "Knowledge Management Systems: Information and Communication Technologies for Knowledge Management (3rd edition)”, Berlin: Springer, 2007. [8] Sanchez, R, “Strategic Learning and Knowledge Management”, Wiley, Chichester, 1996. [9] "Bloomfire"CrunchBase”, Retrieved 17 April 2013. [10] Wright, Kirby, "Personal knowledge management: supporting individual knowledge worker performance". Knowledge Management Research and Practice 3 (3): 156–165, 2005. doi:10.1057/palgrave.kmrp.8500061. [11] Booker, Lorne; Bontis, Nick; Serenko, Alexander, "The relevance of knowledge management and intellectual capital research". Knowledge and Process Management 15 (4): 235–246, 2004. doi:10.1002/kpm.314. [12] Morey, Daryl; Maybury, Mark; Thuraisingham, Bhavani, “Knowledge Management: Classic and Contemporary Works”, MIT Press. pp. 451, 2002. ISBN 0-262-13384-9. [13] McAfee, Andrew, "Enterprise 2.0: The Dawn of Emergent Collaboration". Sloan Management Review 47 (3): 21–28, 2006. [14] Lakhani, Karim; McAfee, Andrew. "Wikipedia's Enterprise 2.0 Article". Harvard Business School, Retrieved 19 April 2013. [15] Davenport, Tom. "Enterprise 2.0: The New, New Knowledge Management?". Harvard Business Review, Retrieved 18 April 2013. [16] McInerney, Claire, "Knowledge Management and the Dynamic Nature of Knowledge", Journal of the American Society for Information Science and Technology 53 (12): 1009– 1018, 2002. doi:10.1002/asi.10109. [17] "Information Architecture and Knowledge Management". Kent State University, Retrieved 18 April 2013. [18] Bray, David. "SSRN-Literature Review – Knowledge Management Research at the Organizational Level". Papers.ssrn.com, Retrieved 18 April 2013. 186
  • 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME [19] Nonaka, Ikujiro, "The knowledge creating company". Harvard Business Review 69 (6): 96– 104, 1991. [20] Stewart, Thomas A., “Intellectual Capital: The New Wealth of Organizations”, Crown Business Publishers, 1998. ISBN 0385483813. [21] Serenko, Alexander; Bontis, Nick; Booker, Lorne; Sadeddin, Khaled; Hardie, Timothy, "A scientometric analysis of knowledge management and intellectual capital academic literature (1994–2008)". Journal of Knowledge Management 14 (1): 13–23, 2010. doi:10.1108/13673271011015534. [22] Langton Robbins, N. S., “Organizational Behaviour”, (Fourth Canadian Edition). Toronto, Ontario: Pearson Prentice Hall, 2006. [23] Alavi, Maryam; Leidner, Dorothy E., "Knowledge management systems: issues, challenges, and benefits", Communications of the AIS 1 (2), 1999. [24] Rosner, D.; Grote, B.; Hartman, K.; Hofling, B.; Guericke, O., "From natural language documents to sharable product knowledge: a knowledge engineering approach". In Borghoff, Uwe M.; Pareschi, Remo. Information technology for knowledge management. Springer Verlag. pp. 35–51, 1998. [25] Bray, David. "SSRN-Knowledge Ecosystems: A Theoretical Lens for Organizations Confronting Hyperturbulent Environments", Papers.ssrn.com. [26] Carlson Marcu Okurowsk, Lynn; Marcu, Daniel; Okurowsk, Mary Ellen, "Building a Discourse-Tagged Corpus in the Framework of Rhetorical Structure Theory", University of Pennsylvania. Retrieved 19 April 2013. [27] "TeacherBridge: Knowledge Management in Communities of Practice", Virginia Tech, Retrieved 18 April 2013. [28] Groth, Kristina. "Using social networks for knowledge management", Royal Institute of Technology, Stockholm, Sweden, Retrieved 18 April 2013. [29] Snowden, Dave, "Complex Acts of Knowing – Paradox and Descriptive Self Awareness". Journal of Knowledge Management, Special Issue 6 (2): 100–111, 2002. [30] Wyssusek, Boris. "Knowledge Management - A Sociopragmatic Approach". CiteSeerX, 2001, Retrieved 18 April 2013. [31] Ferguson, J., "Bridging the gap between research and practice", Knowledge Management for Development Journal 1 (3): 46–54, 2005. [32] Andriessen, Daniel, "Reconciling the rigor-relevance dilemma in intellectual capital research". The Learning Organization 11 (4/5): 393–401, 2004. doi:10.1108/09696470410538288. [33] Hayes, M.; Walsham, G., "Knowledge sharing and ICTs: A relational perspective". In Easterby-Smith, M.; Lyles, M.A., The Blackwell Handbook of Organizational Learning and Knowledge Management. Malden, MA: Blackwell. pp. 54–77, 2003. ISBN 978-0-63122672-7. [34] "Rhetorical Structure Theory Website". RST, Retrieved 19 April 2013. [35] Nonaka, Ikujiro; Takeuchi, Hirotaka, “The knowledge creating company: how Japanese companies create the dynamics of innovation”, New York: Oxford University Press. p. 284. 1995. ISBN 978-0-19-509269-1. [36] Sensky, Tom, "Knowledge Management". Advances in Psychiatric Treatment 8 (5): 387– 395, 2002. doi:10.1192/apt.8.5.387. [37] "SSRN-Exploration, Exploitation, and Knowledge Management Strategies in Multi-Tier Hierarchical Organizations Experiencing Environmental Turbulence by David Bray". Papers.ssrn.com, Retrieved 15 January 2010. 187
  • 7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print), ISSN 0976 - 6375(Online), Volume 4, Issue 5, September - October (2013), © IAEME [38] Bontis, Nick; Choo, Chun Wei, “The Strategic Management of Intellectual Capital and Organizational Knowledge”, New York: Oxford University Press, 2002. ISBN 0-19-513866-X. [39] Benbasat, Izak; Zmud, Robert, "Empirical research in information systems: The practice of relevance", MIS Quarterly 23 (1): 3–16, 1999. doi:10.2307/249403. JSTOR 249403. [40] "Knowledge Management for Data Interoperability", Retrieved 18 April 2013. [41] Alavi, Maryam; Leidner, Dorothy E., "Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues", MIS Quarterly 25 (1): 107–136, 2001. doi:10.2307/3250961. JSTOR 3250961. [42] Wilson, T. D., "The nonsense of 'knowledge management”, Information Research 8 (1), 2002. [43] Jennex, M.E., “Knowledge Management: Concepts, Methodologies, Tools, and Applications. Hershey, PA: IGI Global. pp. 1–3808, 2008. ISBN 978-1599049335. [44] Capozzi, Marla M., "Knowledge Management Architectures Beyond Technology". First Monday 12 (6), 2007. [45] Calvin, D. Andrus, "The Wiki and the Blog: Toward a Complex Adaptive Intelligence Community”, Studies in Intelligence 49 (3), 2005. SSRN 755904. [46] McAdam, Rodney; McCreedy, Sandra, "A Critique of Knowledge Management: Using A Social Constructionist Model", New Technology, Work and Employment 15 (2), 2000. [47] Akscyn, Robert M.; McCracken, Donald L.; Yoder, Elise A., "KMS: A distributed hypermedia system for managing knowledge in organizations", Communications of the ACM 31 (7): 820–835, 1988. [48] Nanjappa, Aloka; Grant, Michael M., "Constructing on constructivism: The role of technology", Electronic Journal for the Integration of Technology in Education 2 (1), 2003. [49] Rajendra S.Pujari, Dr.Pallavi P Jamsendekar and Dr.Rajesh Kanthe, “Knowledge Management System a Panacea for Rural Public Administration”, International Journal of Management (IJM), Volume 4, Issue 2, 2013, pp. 180 - 187, ISSN Print: 0976-6502, ISSN Online: 0976-6510. [50] J.NeelakantaGugesh and Dr.S.SheelaRani, “Influence of Culture in Knowledge Management on Virtual Team”, International Journal of Management (IJM), Volume 2, Issue 2, 2011, pp. 103 - 112, ISSN Print: 0976-6502, ISSN Online: 0976-6510. [51] C.S.Ramanigopal, G.Palaniappan and A.Mani, “Mind Mapping and Knowledge Management: Coding and Implementation of KM System”, International Journal of Management (IJM), Volume 3, Issue 2, 2012, pp. 250 - 259, ISSN Print: 0976-6502, ISSN Online: 0976-6510. AUTHORS’ INFORMATION SHAKTI KUNDU received his MCA from Kurukshetra University Kurukshetra, India in 2006, MPhil in Computer Science from Chaudhary Devi Lal University, Sirsa, Haryana, India in 2008, MTech in Computer Science & Engineering from Guru Jambheshwar University of Science & Technology, Hisar, Haryana, India in 2010. The author current research interests are web mining, knowledge management and web testing. He is life member of CSI, ISTE, IAENG and AIRCC. 188