NDLI: Hiding co-occurring frequent itemsets

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Hiding co-occurring frequent itemsets

Content Provider	ACM Digital Library
Author	Abul, Osman
Abstract	Knowledge hiding, hiding rules/patterns that are inferable from published data and attributed sensitive, is extensively studied in the literature in the context of frequent itemsets and association rules mining from transactional data. The research in this thread is focused mainly on developing sophisticated methods that achieve less distortion in data quality. With this work, we extend frequent item-set hiding to co-occurring frequent itemset hiding problem. Co-occurring frequent itemsets are those itemsets that co-exist in the output of frequent itemset mining. What is different from the classical frequent hiding is the new sensitivity definition: an itemset set is sensitive if its itemsets appear altogether within the frequent item-set mining results. In other words, co-occurrence is defined with reference to the mining results but not to the raw input dataset, and thus it is a kind of meta-knowledge. Our notion of co-occurrence is also very different from association rules as itemsets in an association rule need to be frequently present in the same set of transactions, but the co-occurrence need not necessarily require the joint occurrence in the same set of transactions. In this paper, we briefly review the frequent itemset/association hiding problems and define the co-occurrence hiding along with the real world motivations. We explore its fundamental properties and show that frequent itemset hiding is a special case of the co-occurring frequent itemsets hiding. As a solution, we propose a two-stage sanitization framework, essentially a reduction, where an instance of the frequent itemset hiding is constructed in the first stage and the instance is solved in the second stage. Since the task is shown to be NP-Hard and the reduction is one-to-many, we propose heuristics only for the first stage as the second stage is a well-established field. Finally, an experimental evaluation is carried out on a couple of datasets, and the results are presented.
Starting Page	117
Ending Page	125
Page Count	9
File Format	PDF
ISBN	9781605586502
DOI	10.1145/1698790.1698810
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2009-03-22
Publisher Place	New York
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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