Explain multimedia database in brief. What are the different applications of multimedia database?

-

 Multimedia Database 

A Multimedia database is the collection of interrelated multimedia data that includes text, graphics (sketches, drawings), images, animations, video, audio, etc., and has 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 a multimedia database management system.

Multimedia databases provide features that allow users to store and query different types of multimedia information, which includes images (such as photos or drawings), video clips (such as movies, newsreels, or home videos), audio clips (such as songs, phone messages, or speeches), and documents (such as books or articles). The main types of database queries that are needed involve locating multimedia sources that contain certain objects of interest. For example, one may want to locate all video clips in a video database that includes a certain person, say Michael Jackson. One may also want to retrieve video clips based on certain activities included in them, such as video clips where a soccer goal is scored by a certain player or team. The contents of a multimedia database management system can be:
Media data: It is the actual data that represents an object. Media format data: The information such as resolution, sampling rate, encoding system, etc. about the format of the media data under consideration after it undergoes acquisition, processing, and encoding is the media format data.

Media keyword data: Media keyword data are the keyword description related to the generation of data. This data is also known as content descriptive data. Examples of content descriptive data are place, time, and date of recording.

Media feature data: Media feature data contains data that is content dependent such as kind of texture, distribution, and the different shapes present in the data.

Multimedia Database Applications

Documents and record management: Industries that keep a lot of documentation and records. Ex: Insurance claim industry.

Knowledge dissemination: Multimedia database is an extremely efficient tool for knowledge dissemination and providing several resources. Ex: electronic books

Education and training: Multimedia sources can be used to create resources useful in education and training. These are popular sources of learning in recent days. Ex: Digital libraries.

Real-time monitoring and control: Multimedia presentation when coupled with active database technology can be an effective means for controlling and monitoring complex tasks. Ex: Manufacture control

  1. Marketing
  2. Advertisement
  3. Retailing
  4. Entertainment
  5. Travel


Comments

Post a Comment

Popular posts from this blog

Suppose that a data warehouse for Big-University consists of the following four dimensions: student, course, semester, and instructor, and two measures count and avg_grade. When at the lowest conceptual level (e.g., for a given student, course, semester, and instructor combination), the avg_grade measure stores the actual course grade of the student. At higher conceptual levels, avg_grade stores the average grade for the given combination. a) Draw a snowflake schema diagram for the data warehouse. b) Starting with the base cuboid [student, course, semester, instructor], what specific OLAP operations (e.g., roll-up from semester to year) should one perform in order to list the average grade of CS courses for each BigUniversity student. c) If each dimension has five levels (including all), such as “student < major < status < university < all”, how many cuboids will this cube contain (including the base and apex cuboids)?

-
Image
a) A Snowflake Shema is shown in figure below: b) The specific OLAP operations to be performed: 1. Roll-up on course from course_id to department. 2. Roll-up on a student from student_id to university. 3. Dice on course, student with department ="CS" and university = "biguniversity" 4. Drill-down on a student from the university to student_name. c) N = 4 dimensions The cube will contain 54 = 625 cuboids.
Read more

Suppose that a data warehouse consists of the four dimensions; date, spectator, location, and game, and the two measures, count and charge, where charge is the fee that a spectator pays when watching a game on a given date. Spectators may be students, adults, or seniors, with each category having its own charge rate. a) Draw a star schema diagram for the data b) Starting with the base cuboid [date; spectator; location; game], what specific OLAP operations should perform in order to list the total charge paid by student spectators at GM Place in 2004?

-
Image
  b) The specific OLAP operations to be performed are: 1. Roll-up on date from date id to year. 2. Roll-up on spectator from spectator id to status. 3. Roll-up on location from location id to location name. 4. Roll-up on the game from game id to all. 5. Dice with status= “students”, location name= “GM Place”, and year=2004
Read more

What is national data warehouse? What is census data?

-
Image
National Data warehouse   A large number of national data warehouses can be identified from the existing data resources within the central government ministries. These are potential subject areas in which data warehouses may be developed at present and in the future. Census Data Census data can help planners and others understand their communities' social, economic, and demographic conditions. Census data is the primary data used by planners to understand the social, economic, and demographic conditions locally and nationally. We sometimes think the census is unique to the United States, but census data is collected in other countries.  The total process of collecting, compiling, and publishing demographic, economic, and social data about a specific time to all people in a country or fixed or defined area part of a country. Most countries also include a housing census. A census is a procedure of systematically acquiring and recording information about the members of a given populat
Read more