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.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 - Scopus: 2Adaptive Join Operator for Federated Queries Over Linked Data Endpoints(Springer Verlag, 2016) Oğuz, Damla; Yin, Shaoyi; Hameurlain, Abdelkader; Ergenç, Belgin; Dikenelli, OğuzTraditional static query optimization is not adequate for query federation over linked data endpoints due to unpredictable data arrival rates and missing statistics. In this paper, we propose an adaptive join operator for federated query processing which can change the join method during the execution. Our approach always begins with symmetric hash join in order to produce the first result tuple as soon as possible and changes the join method as bind join when it estimates that bind join is more efficient than symmetric hash join for the rest of the process. We compare our approach with symmetric hash join and bind join. Performance evaluation shows that our approach provides optimal response time and has the adaptation ability to the different data arrival rates.