The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Matching Attributes across Overlapping Heterogeneous Data Sources Using Mutual Information
Abstract
Identifying matching attributes across heterogeneous data sources is a critical and time-consuming step in integrating the data sources. In this paper, the author proposes a method for matching the most frequently encountered types of attributes across overlapping heterogeneous data sources. The author uses mutual information as a unified measure of dependence on various types of attributes. An example is used to demonstrate the utility of the proposed method, which is useful in developing practical attribute matching tools.
Related Content
|
Renjith V. Ravi, Mangesh M. Ghonge, P. Febina Beevi, Rafael Kunst.
© 2022.
24 pages.
|
|
Manimaran A., Chandramohan Dhasarathan, Arulkumar N., Naveen Kumar N..
© 2022.
20 pages.
|
|
Ram Singh, Rohit Bansal, Sachin Chauhan.
© 2022.
19 pages.
|
|
Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka.
© 2022.
17 pages.
|
|
Vladimir Nikolaevich Kustov, Ekaterina Sergeevna Selanteva.
© 2022.
23 pages.
|
|
Krati Reja, Gaurav Choudhary, Shishir Kumar Shandilya, Durgesh M. Sharma, Ashish K. Sharma.
© 2022.
18 pages.
|
|
Nwosu Anthony Ugochukwu, S. B. Goyal.
© 2022.
23 pages.
|
|
|