You are here

Home » Content

INTERDISCIPLINARY RESEARCH ON KNOWLEDGE DISCOVERY DATABASES WITH HIGHLY INTERACTIVE HUMAN CANTERED ENVIRONMENTS

Journal Name:

  • Review Of Research

Publication Year:

  • 2013

Keywords (Original Language):

Author Name
Bookmark/Search this post with
Abstract (Original Language): 
This paper describe the role of domain expert in the process of Knowledge Discovery in Databases (KDD). In order to get better results, various steps of knowledge discovery process are extended with the domain specific expertise of the users. Intermediate results after each step are provided to the domain expert to check whether the process is proceeding in the right direction or there exists a need to change certain variables [Ankerest M., 2001; Hellerstein J.M. et.al., 1999; Anand S.S. et.al.,1995].Even though the quality of results heavily relies on data preparation. Preparing data includes data selection, data cleaning, data transformation and data validation etc. These initial steps of exploring, visualizing and querying the data, to gain insight into the data are very vital and are better done in an interactive manner.
FULL TEXT (PDF): 
PDF icon arastirmax-interdisciplinary-research-knowledge-discovery-databases-highly-interactive-human-cantered-environments.pdf
  • 6
1
7
  • English

REFERENCES

References: 

1) Adriaans P. and Zantinge D. (2003). Data Mining. Pearson Education, Seventh Indian Reprint, 2003.
2) Agrawal R. and Srikant R. (1994). Fast Algorithms for Mining Association Rule. Proceedings of the 20th
International Conference on Very Large Databases (VLDB), 487 – 499.
3) Agrawal R., Faloutsos C. and Swami A. (1993). Efficient similarity search in sequence databases.
Proceedings of the Fourth International Conference on Foundations of Data Organization and Algorithms,
Chicago, Vol. 730, 69-84.
4) Agrawal R., Imielinski T. and Swami A. (1993). Mining association rules between sets of items in large
databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data,
Washington DC, 207-216.
5) Ahmed S.R. (2007). Applications of Data Mining in Retail Business. International Conference on
Information Technology: Coding and Computing, Las Vegas, Nevada, Vol. 2.
6) Anand S.S., Bell D.A. and Hughes J.G. (1995). The Role of Domain Knowledge in Data Mining.
Proceedings of the Fourth International Conference on Information and knowledge management, 37-43.
6) Ankerest M. (2001). Human Involvement and Interactivity of the Next generation's Data Mining Tools.
ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery. Santa Barbara,
CA.
7) Ankerest M., Ester M. and Kriegel H.P. (2000). Towards an Effective Cooperation of the User and the
Computer for Classification. Proceedings of 6th International conference on Knowledge Discovery and
Data Mining, Boston, MA.

Thank you for copying data from http://www.arastirmax.com