READIT-2007 - Indira Gandhi Centre for Atomic Research

7. A private or public network.
2. DIGITIZATION AND DATA MINING
Digitization refers to the conversion of an item – be it printed text, manuscript, image
or sound, film and video recording – from one format (usually print or analogue) into digital.
The process basically involves taking a physical object and essentially making an ‘electronic
photograph’ of it. An image of the physical object is captured- using a scanner or digital
camera – and converted to digital format that can be stored electronically and accessed via a
computer 2 .
It is noted that the data and information available in different formats. These formats
include Text, Images, Video, Audio, Picture, Maps, etc. It is noted that in case of text
information, there is needed to scan the printed text through scanners and provide different
links to access it. But in case of multimedia formats like images, Audio, Picture, Maps,
Video etc, the conversion and systematic presentation is not easy. Further, there is needed to
make automatic search for easy accessibility. The easy search, effective and systematic
presentation of the data is essential in case of multimedia information. For this purpose, there
is need to adopt data mining techniques in the library. Data mining techniques are basically
from logic, Multimedia and Artificial Intelligence techniques.
Data mining is the automatic extraction of patterns of information from historical
data, enabling companies to focus on the next important aspects of their business—telling
them what they did not know and had not even thought of asking 3 . Data mining is that it “is
the process of automating information discovery” 4 , which improves decision making and
gives a company advantages on the market. Another definition is that is “is the exploration
and analysis, by automatic or semiautomatic means, of large quantities of data in order to
discover meaningful patterns and rules: 5 Data mining is an applied discipline, which grew
our of the statistical pattern recognition, machine learning, and artificial intelligence and
coupled with business decision making to optimize and enhance it. Initially, data mining
techniques have been applied to structured data from databases.
Recently two branches of data mining, text data mining and Web data mining, have
emerged 6&7 . They have their own research agenda, communities of researchers, and
supporting companies that develop technologies and tools. Unfortunately, today multimedia
data mining is in beginning stage and still there is need for developments to make effective
presentation of multimedia information.
There are four types of multimedia data: audio data, which includes sound , speech,
and music; image data (black-and-white and colour images); video data, which include timealigned
sequences of images; and electronic or digital, which is sequences of time aligned 2D
or 3D coordinates of a stylus, a light per, data glove sensors, or a similar device. All this data
is generated by specific kind of sensors.
The concept of mining in multimedia is also referred to as automatic annotation or
annotation mining. There appears to be three main pattern discovery approaches that have
been used for automatic annotation in multimedia data mining. These approaches primarily
differ in terms of how external knowledge is provided to mine concepts. The first approach
includes assigning key words or classifying the data. The second approach for automatic
annotation is through clustering and here multimedia documents are clustered first and then
the resulting clusters are assigned keywords by annotator. The third approach does not rely
on manual annotator and it tries to mine concepts by knowing the contextual information.
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