Unit 8



1)      What is informational data store? Briefly describe the characteristics of informational data.

2)      Briefly discuss about document classification

3)      What is spatial database and what is data mining? What is spatial OLAP? Describe the dimensions and measure in spatial data cube?

4)      What is text mining? Describe about basic measures for text retrieval? What methods are there for information retrieval?

5)      What is structured data? How generalization can be performed on structured data?

6)      What is multimedia data mining? How similarity search can be performed on multimedia data? Describe the contents of a multimedia data

7)      What is authoritative web page? Briefly describe web usage mining.


What is meant by authoritative web pages? Explain about mining the web link structures to identify authoritative web pages.

8)      What is multimedia data? Briefly describe the similarity search in multimedia data.

9)      What is multimedia data mining? What kind of associations can be mined in multimedia data?

10)  What is multimedia database? Explain mining multimedia database?

11)  What is informal data store? Briefly describe the characteristics of informational data.

12)  What is WWW and multimedia data? What is meant by authoritative web page? Describe web usage mining.

13)  Define influence function, density function and square wave function.

14)  What is spatial data and what is time series data? Briefly describe time series and sequence data mining.

15)  Explain similarity search in multimedia and time series analysis.

16)  What are different approaches for similarity based retrieval in image database

17)  Explain the classification and prediction analysis of multimedia data.

18)  What is spatial data warehouse? What are different types of dimensions in a spatial data cube? What are the different types of measures in a spatial data cube?

19)  What is keyword based association analysis? How can automated document classification be performed?

20)  Explain the following:

                 a) Construction of a multilayered web information base.

                  b) Text mining

                  c) Periodicity analysis.

                  d) Characterization of time-series data.

20) Explain the following:

           a) Construction and mining of object cubes.

            b) Similarity search in multimedia data.

            c) Sequential pattern mining

            d) Inverted index.

21) Explain the following:

            a) Keyword based association analysis

             b) Latent semantic indexing

             c) Mining association in multimedia data

              d) Spatial data cube construction

22) Explain the following:

       a) Generalization of structured data.

       b) Spatial association analysis.

       c) Basic methods of text retrieval

       d) Web usage mining.

23) An e-mail databases is a database that stores a large number of electronic mail messages. It can be viewed as a semi structured database consisting mainly of text data. Discuss the following

 a) How can such an e-mail database be structured so as to facilitate multidimensional search. Such as by sender, by   receiver, by subject, by time, and so on.

b) What can be mined from such an email databases?

c) Suppose you have roughly classified a set of your previous e-mail message as junk, unimportant, normal, or important. Describe how a data mining system may take this as the training set to automatically classify new e-mail messages or unclassified ones.

24) Suppose that a city transportation department would like to perform data analysis on highway traffic for planning of highway construction based on the city traffic data collected at different hours a day.

      a) Design a spatial data warehouse that stores the highway traffic information so that   people can easily see the average and peak time traffic flow by highway, by time of day, and by weekdays, and the traffic situation when a major accident occurs.

     b) What information can we mine from such a spatial data warehouse to help city planners?

     c) This data warehouse contains both spatial and temporal data. Propose one mining technique that can efficiently mine interesting patterns from such a spatio –temporal data warehouse

25) Explain the following:

                a) Construction and mining of object cubes

                 b) Mining association in multimedia data

                  c) Periodicity analysis

                   d) Latent semantic indexing.

26) Give an example of generalization based mining of plan databases by divide and conquer.

27) What is sequential pattern mining? Explain. ……4

28) Explain the construction of a multilayered web information base.

30) write a short note on mining the www.



    Write something about yourself. No need to be fancy, just an overview.


    March 2012