DBMS |
Multimedia Database
Multimedia database is the collection of interrelated multimedia data that
includes text, graphics (sketches, drawings), images, animations, video, audio
etc and have vast amounts of multisource multimedia data. The framework that
manages different types of multimedia data which can be stored, delivered and
utilized in different ways is known as multimedia database management system.
There are three classes of the multimedia database which includes static media,
dynamic media and dimensional media.
Content of Multimedia Database management system :
1.
Media
data – The actual data
representing an object.
2.
Media
format data – Information such
as sampling rate, resolution, encoding scheme etc. about the format of the
media data after it goes through the acquisition, processing and encoding
phase.
3.
Media
keyword data – Keywords
description relating to the generation of data. It is also known as content
descriptive data. Example: date, time and place of recording.
4.
Media
feature data – Content dependent
data such as the distribution of colors, kinds of texture and different shapes
present in data.
Types of multimedia applications based on data management
characteristic are :
1.
Repository
applications – A Large amount of
multimedia data as well as meta-data(Media format date, Media keyword data,
Media feature data) that is stored for retrieval purpose, e.g., Repository of
satellite images, engineering drawings, radiology scanned pictures.
2.
Presentation
applications – They involve
delivery of multimedia data subject to temporal constraint. Optimal viewing or
listening requires DBMS to deliver data at certain rate offering the quality of
service above a certain threshold. Here data is processed as it is delivered.
Example: Annotating of video and audio data, real-time editing analysis.
3.
Collaborative
work using multimedia information – It involves executing a complex task by merging drawings,
changing notifications. Example: Intelligent healthcare network.
There are still many challenges to multimedia databases, some of
which are :
1.
Modelling
– Working in this
area can improve database versus information retrieval techniques thus,
documents constitute a specialized area and deserve special consideration.
2.
Design
– The conceptual,
logical and physical design of multimedia databases has not yet been addressed
fully as performance and tuning issues at each level are far more complex as
they consist of a variety of formats like JPEG, GIF, PNG, MPEG which is not
easy to convert from one form to another.
3.
Storage
– Storage of
multimedia database on any standard disk presents the problem of
representation, compression, mapping to device hierarchies, archiving and
buffering during input-output operation. In DBMS, a ”BLOB”(Binary Large Object)
facility allows untyped bitmaps to be stored and retrieved.
4.
Performance
– For an application
involving video playback or audio-video synchronization, physical limitations
dominate. The use of parallel processing may alleviate some problems but such
techniques are not yet fully developed. Apart from this multimedia database
consume a lot of processing time as well as bandwidth.
5.
Queries
and retrieval –For multimedia data like
images, video, audio accessing data through query opens up many issues like
efficient query formulation, query execution and optimization which need to be
worked upon.
Areas where multimedia database is applied are :
§
Documents
and record management : Industries
and businesses that keep detailed records and variety of documents. Example:
Insurance claim record.
§
Knowledge
dissemination : Multimedia
database id a very effective tool for knowledge dissemination in terms of
providing several resources. Example: Electronic books.
§
Education
and training : Computer-aided
learning materials can be designed using multimedia sources which are nowadays
very popular sources of learning. Example: Digital libraries.
§
Marketing, advertising,
retailing, entertainment and travel. Example: a virtual tour of cities.
§
Real-time
control and monitoring : Coupled
with active database technology, multimedia presentation of information can be
very effective means for monitoring and controlling complex tasks Example:
Manufacturing operation control.
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Introduction to Web
Databases
General: Main page Relational Databases Object Oriented Databases Web
Databases
Applications: Oracle IBM DB2 Access
Other : On Linux
Applications: Oracle IBM DB2 Access
Other : On Linux
"This shouldn't be
hard", you think to yourself. You want to buy a computer, so you figure
the Internet is the best place to look. You get on Alta Vista, and type
"computers" in the text box. It comes back and tells you that it has
found about 1 million pages matching your query terms. You try another tactic -
you type in "I want to buy a computer". Only 400,000 pages this time
- and glancing at the descriptions for the first 10 pages, you see places to
buy Liberal Bumper Stickers, Foreign Currency, even a Volkswagen, but nothing
about buying computers. Frustrated, you try one more time - you type in
"computer shopping". Alta Vista happily tells you there are 700,000
pages matching your request. The first listing is indeed about shopping for
computers - and the rest on the page refer to on-line malls.
Does this sound
familiar? If you've done any amount of Web searching, you've undoubtedly run
into this same problem of too much information. This tutorial will you by
showing you how these Web Databases work, how you can more efficiently search
them, and how to select the best Web Database using the AskScott selection
tool.
A web database is an
organized listing of web pages. It's like the card catalog that you might find
in the library. The database holds a "surrogate" (or selected pieces
like the title, the headings, etc.) for each web page. The creation of these
surrogates is called "indexing", and each web database does it in a
different way. Web databases hold surrogates for anywhere from 1 to 30 million
web pages. The program also has a search interface, which is the box you type
words into (like in Alta Vista or Lycos) or the lists of directories you pick
from (like in Yahoo). Thus, each web database has a different indexing method
and a different search interface.
There are three methods
of indexing used in web database creation - full-text, keyword, and human.
Full-Text Indexing
As its name implies,
full-text indexing is where every word on the page is put into a database for
searching. Alta Vista and Open Text are examples of full-text databases.
Full-text indexing will help you find every examples of a reference to a
specific name or terminology. However, a general topic search will not be very
useful in these database, and you will have to dig through a lot of "false
drops" (or returned pages that have nothing to do with your search).
Keyword Indexing
In keyword indexing,
only the "important" words and phrases are put into the database.
Lycos and Excite are keyword indexed. This allows a searcher to search on more
general subjects and have more accurate results. However, if a name is only mentioned
once or twice on a page, it won't be included in the database.
Human Indexing
Yahoo and some of
Magellan are two of the few examples of human indexing. In the above two
indexing, all of the work was done by a computer program called a
"spider" or a "robot". In human indexing, a person examines
the page and determines a very few key phrases that describe it. This allows
for the user to find a good start of works on a topic - assuming that the topic
was picked by the human as something that describes the page. This is how the
directory-based web databases are developed.
How do the web databases
select which pages are indexed? As there is no centralized Internet computer,
there's no one place where these services can learn about new pages. Thus, many
services use automated programs called "spiders" or
"robots" that travel from site to site, looking for new WWW pages.
Some spiders only go to the "What's New" or the "What's
Hot" pages and use those for indexing the "popular" sites.
Others methodically examine every link leading from a page, and every link
leading from that page, and so on... In some cases, people examine the pages
brought back from these programs, and don't index the pages that don't meet
certain criteria. So, these tools create three classes of web databases - those
that look at all WWW pages, those that examine popular WWW pages, and those
that examine quality web pages.
Now that the web
database has a group of pages indexed in their database, how does the user
access it. This is through one of two methods - a search engine or a
directory (otherwise known as a pick list). A search engine allows the user to
type in any terminology he wishes, and will search the database to find those
web pages that match the terms entered. A directory structure has pages
organized by subject (like the Yellow Pages), and can then be navigated by
selecting things off the directory. The directory structure usually allows a
good starting point for a search, assuming that the topic you desire has been
selected as a directory entry.
One thing not to get
confused about - Yahoo has both a search engine and a directory tree. Instead
of searching the pages, however, the search engine just looks through the
directory at Yahoo. It can be used as a quick way to find the area of the
directory with the information you desire.
You've entered in your
search terms, the computer has matched them to the indexed database, and you
are given a list of results. There are two important concepts here - Relevancy
ranking and Abstracts
Relevancy Ranking
The documents are almost
always listed in order by relevance. Based upon your search request, the
computer ranks all of the documents that contain your search term, and lists
the ones that it thinks are most relevant first. That is why you
really shouldn't worry about the fact that there are 17 gajillion pages
matching your query term. All you care about are the first 20 - 40. The better
your search terms, the better ranked the pages will be (and the less work you
will have to do).
Abstracts
If there are pages
listed that say nothing in the listing about your search topic, you may wonder
how they got there. The second important concept to realize is that the
abstract presented to you is usually not the same as the
database entry used by the computer to search. The abstract is much shorter
than the database entry, and this can lead to frustration because you then have
to load up the actual page to see why the search program feels this page is
relevant to your search.
Each web database is
different, and searching in one not appropriate for your search term can be
very frustrating. That is where AskScott helps. By telling AskScott if you
have a general or specific search topic, whether you want to type in your
request or pick from a directory structure, and whether you are looking for all
pages, popular pages, or quality pages, AskScott will tell you which database
is best for you!
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