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Knowledge
Discovery in Database
--S
Sudeesh
A
database system, at its core, reduced to its basic components,
consists of data, hardware and software. Computer hard disks
and memories show increased capacity and reduced cost each
year. Since the cost of data storage keeps on dropping, users
store all the information they need in databases. This write
up may give some insight about knowledge discovery in databases
and data mining, the usage and the very purpose of KDD and
some methods of discovering the knowledge from databases.
©
2004 IUP. All Rights Reserved.
An
Approach to Establish Data Warehouse
for Banks in India
--Dr.
P Radha Krishna
Operational
data is the source for all business intelligence applications,
but the data is typically not in the correct format to support
the decision-making process in a business. Further, nowadays,
banks are storing more information than ever before. Decision
makers must have the right information at the right time to
help them make more informed and intelligent decisions. The
data in the operational database represents current transactions,
however, the decisions are based on a different time frame.
Moreover, data in operational databases are stored with a
functional or process orientation and what really decision
makers would like to have is subject orientation of data,
which facilitates multiple views for data and decision making.
Data Warehousing and Data Mining are the right solution that
makes the above possible. One of the main goals of implementing
a data warehouse is to turn the wealth of corporate data into
information that can be used in the daily decision making
process. In this paper, we highlight the need of data warehousing
and data mining for banks and provide an approach to build
the warehouse suitable to banks.
©
2004 IUP. All Rights Reserved.
Information
Retrieval in Digital Library Research: A
Survey Towards Knowledge Perspective
--N
Girija and Dr. S K Srivatsa
We
are living in an age of `information explosions'. The explosion
which reigns supreme is the `knowledge explosion'. So, Information
is congregated, processed, organized, stored and disseminated
in different forms and media. Not all information is valuable.
A Knowledge Management is to identify and disseminate knowledge
gems from a sea of information. Therefore, it is imperative
to identify what information is qualifying for intellectual
and knowledgebased assets. For this purpose, phenomenal growth
of library materials are to be scanned and converted into
digital format either as text or image and stored in CD-ROMs,
servers etc. for easy retrieval. For Digital Library Research,
this means that in addition to resource discovery and retrieval,
informal information transfer among on-line, human and other
off-line sources need support. The Digital Library Research
is at the crossroad of research from several research communities
such as database especially Multimedia database, Information
Retrieval, Natural Language Processing(NLP), Web Mining, Artificial
Intelligence, Digital Object Identifiers and Digital Rights
Management. For this study, the focus is on knowledge management,
through information retrieval, keeping as the primary goals,
indexing of text and searching for useful documents in a collection.
And the concentration is in information retrieval on three
major areas covering Query-based, Link Analysis, and Semantic
Web and Languages. There are also other methods of information
retrieval like Tree structure, Key phrases, Machine-learning
Algorithm etc. The concluding part of this paper highlights
some probable research issues related to the present study.
©
2004 IUP. All Rights Reserved.
Web
Mining Technology : Human-Machine Connections
--R
Senkamalavalli and G Mythili
The
uncertainties of the Internet not only challenge the modern
workspace but also promise unexpected opportunities. Converting
uncertainties into opportunities requires human efforts to
enhance the capabilities of technology. In order to adapt
to the new climate of the information World, professionals
of all disciplines are charged to extend their services from
the reference desk to the virtual environment on the World
Wide Web. Hence, professionals, in particular, experts of
medical field are constantly investigating new information
technologies that can assist in organizing and retrieving
information. Web mining is one of the critical tools for competitive
application intelligence. It refers to the discovery and analysis
of data, documents and multimedia from the World Wide Web.
This paper focuses on human-machine connections between medical
professionals and web mining technology. Further, it explores
ways of converting the uncertainty of symptoms of diseases
and the web information explosion to opportunities for advancing
medical professionals' services. The improvement of electronic
reference services will strongly support the experts. A well-designed
process of human machine connection becomes virtually important.
The speculative process of web mining, supporting medical
expert's mission, has been explained with a scenario.
© 2004 IUP. All Rights Reserved.
Modeling
Urban Traffic Systems Using OO-Methodology of UML
--Dr.
Vipin Saxena and Manuj Darbari
This
paper proposes an object-oriented modeling methodology, which
is based on global and structured UTS modeling approach, using
UML. We show how UML diagrams are used in our methodology
and why. The first part of this paper is dedicated to the
domain analysis and shows which diagram to use. In the second
part, we deal with system dedicated analysis. We then present
a real case study we have dealt with.
© 2004 IUP. All Rights Reserved.
In-process
Metrics for Software Testing
--S
H Kan, J Parrish and D Manlove
In-process
tracking and measurements play a critical role in software
development, particularly for software testing. Although there
are many discussions and publications on this subject and
numerous proposed metrics, few in-process metrics are presented
with sufficient experiences of industry implementation to
demonstrate their usefulness. This paper describes several
inprocess metrics whose usefulness has been proven with ample
implementation experiences at the IBM Rochester AS/400®
software development laboratory. For each metric, we discuss
its purpose, data, interpretation, and use and present a graphic
example with real-life data. We contend that most of these
metrics, with appropriate tailoring as needed, are applicable
to most software projects and should be an integral part of
software testing.
@
2001 International Business Machines Corporation. This was
previously published in IBM Systems journal, Vol. 40, No.1,
2001. Reprinted with permission
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