Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 4Citation - Scopus: 5Dma: Matrix Based Dynamic Itemset Mining Algorithm(IGI Global Publishing, 2013) Oğuz, Damla; Yıldız, Baroş; Ergenç, BelginUpdates on an operational database bring forth the challenge of keeping the frequent itemsets up-to-date without re-running the itemset mining algorithms. Studies on dynamic itemset mining, which is the solution to such an update problem, have to address some challenges as handling i) updates without re-running the base algorithm, ii) changes in the support threshold, iii) new items and iv) additions/deletions in updates. The study in this paper is the extension of the Incremental Matrix Apriori Algorithm which proposes solutions to the first three challenges besides inheriting the advantages of the base algorithm which works without candidate generation. In the authors' current work, the authors have improved a former algorithm as to handle updates that are composed of additions and deletions. The authors have also carried out a detailed performance evaluation study on a real and two benchmark datasets.Conference Object Citation - WoS: 2Citation - Scopus: 2Dynamic Itemset Mining Under Multiple Support Thresholds(IOS Press, 2016) Abuzayed, Nourhan; Ergenç Bostanoğlu, Belgin; Ergenç, BelginHandling dynamic aspect of databases and multiple support threshold requirements of items are two important challenges of frequent itemset mining algorithms. Existing dynamic itemset mining algorithms are devised for single support threshold whereas multiple support threshold algorithms assume that the databases are static. This paper focuses on dynamic update problem of frequent itemsets under MIS (Multiple Item Support) thresholds and introduces Dynamic MIS algorithm. It is i) tree based and scans the database once, ii) considers multiple support thresholds, and iii) handles increments of additions, additions with new items and deletions. Proposed algorithm is compared to CFP-Growth++ and findings are; in dynamic database 1) Dynamic MIS performs better than CFP-Growth++ since it runs only on increments and 2) Dynamic MIS can achieve speed-up up to 56 times against CFP-Growth++.Article Citation - WoS: 1Citation - Scopus: 2Dynamic Itemset Hiding Algorithm for Multiple Sensitive Support Thresholds(IGI Global, 2018) Öztürk, Ahmet Cumhur; Ergenç, BelginThis article describes how association rule mining is used for extracting relations between items in transactional databases and is beneficial for decision-making. However, association rule mining can pose a threat to the privacy of the knowledge when the data is shared without hiding the confidential association rules of the data owner. One of the ways hiding an association rule from the database is to conceal the itemsets (co-occurring items) from which the sensitive association rules are generated. These sensitive itemsets are sanitized by the itemset hiding processes. Most of the existing solutions consider single support thresholds and assume that the databases are static, which is not true in real life. In this article, the authors propose a novel itemset hiding algorithm designed for the dynamic database environment and consider multiple itemset support thresholds. Performance comparisons of the algorithm is done with two dynamic algorithms on six different databases. Findings show that their dynamic algorithm is more efficient in terms of execution time and information loss and guarantees to hide all sensitive itemsets.Article Citation - WoS: 1Citation - Scopus: 1Extended Adaptive Join Operator With Bind-Bloom Join for Federated Sparql Queries(IGI Global Publishing, 2017) Oğuz, Damla; Yin, Shaoyi; Ergenç, Belgin; Hameurlain, Abdelkader; Dikenelli, OğuzThe goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.Conference Object Citation - WoS: 7Citation - Scopus: 20Vertical Pattern Mining Algorithm for Multiple Support Thresholds(Elsevier Ltd., 2017) Darrab, Sadeq; Ergenç Bostanoğlu, Belgin; Ergenç, BelginFrequent pattern mining is an important task in discovering hidden items that co-occur (itemset) more than a predefined threshold in a database. Mining frequent itemsets has drawn attention although rarely occurring ones might have more interesting insights. In existing studies, to find these interesting patterns (rare itemsets), user defined single threshold should be set low enough but this results in generation of huge amount of redundant itemsets. We present Multiple Item Support-eclat; MIS-eclat algorithm, to mine frequent patterns including rare itemsets under multiple support thresholds (MIS) by utilizing a vertical representation of data. We compare MIS-eclat to our previous tree based algorithm, MISFP-growth28 and another recent algorithm, CFP-growth++22 in terms of execution time, memory usage and scalability on both sparse and dense databases. Experimental results reveal that MIS-eclat and MISFP-growth outperform CFP-growth++ in terms of execution time, memory usage and scalability.Article Citation - WoS: 17Citation - Scopus: 26Federated Query Processing on Linked Data: a Qualitative Survey and Open Challenges(Cambridge University Press, 2015) Oğuz, Damla; Ergenç, Belgin; Yin, Shaoyi; Dikenelli, Oğuz; Hameurlain, AbdelkaderA large number of data providers publish and connect their structured data on the Web as linked data. Thus, the Web of data becomes a global data space. In this paper, we initially give an overview of query processing approaches used in this interlinked and distributed environment, and then focus on federated query processing on linked data. We provide a detailed and clear insight on data source selection, join methods and query optimization methods of existing query federation engines. Furthermore, we present a qualitative comparison of these engines and give a complementary comparison of the measured metrics of each engine with the idea of pointing out the major strengths of each one. Finally, we discuss the major challenges of federated query processing on linked data. © 2015 Cambridge University Press.Article Citation - WoS: 3Citation - Scopus: 4Full-Exact Approach for Frequent Itemset Hiding(IGI Global Publishing, 2015) Ayav, Tolga; Ergenç, BelginThis paper proposes a novel, exact approach that relies on integer programming for association rule hiding. A large panorama of solutions exists for the complex problem of itemset hiding: from practical heuristic approaches to more accurate exact approaches. Exact approaches provide better solutions while suffering from the lack of performance and existing exact approaches still augment their methods with heuristics to make the problem solvable. In this case, the solution may not be optimum. This work present a full-exact method, without any need for heuristics. Extensive tests are conducted on 10 real datasets to analyze distance and information loss performances of the algorithm in comparison to a former similar algorithm. Since the approach provides the optimum solution to the problem, it should be considered as a reference method.Conference Object Citation - WoS: 4Citation - Scopus: 6Robust Placement of Mobile Relational Operators for Large Scale Distributed Query Optimization(Institute of Electrical and Electronics Engineers Inc., 2007) Ergenç, Belgin; Morvan, Franck; Hameurlain, AbdelkaderThis paper presents a compile-time placement method of mobile relational operators MROs in a large scale environment. MROs are self adaptive to changing runtime conditions by deciding their execution place if they discover compile-time estimation errors. Proposed placement methods tend to have a main drawback with MROs running over a large scale environment: their focus is on finding optimal performance depending on single-point estimation at compile-time, instead of optimal performance over an estimation interval. We propose: (i) to determine the migration space of a MRO including the sites on which the MRO is allowed to migrate during its execution, and (ii) to find the robust site which will allow acceptable response time in an estimation interval. Performance study shows that, with a risk of loosing around 6% in response time, it is possible to gain up to 300% with the proposed robust placement.