The Experts below are selected from a list of 3021 Experts worldwide ranked by ideXlab platform
Jerry Chunwei Lin - One of the best experts on this subject based on the ideXlab platform.
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dynamic maintenance model for high average utility pattern mining with Deletion Operation
Applied Intelligence, 2021Co-Authors: Qian Teng, Shahab Tayeb, Jerry Chunwei LinAbstract:The high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/Deletion Operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the Deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction Deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction Deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.
Qian Teng - One of the best experts on this subject based on the ideXlab platform.
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dynamic maintenance model for high average utility pattern mining with Deletion Operation
Applied Intelligence, 2021Co-Authors: Qian Teng, Shahab Tayeb, Jerry Chunwei LinAbstract:The high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/Deletion Operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the Deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction Deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction Deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.
Shahab Tayeb - One of the best experts on this subject based on the ideXlab platform.
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dynamic maintenance model for high average utility pattern mining with Deletion Operation
Applied Intelligence, 2021Co-Authors: Qian Teng, Shahab Tayeb, Jerry Chunwei LinAbstract:The high average-utility itemset mining (HAUIM) was established to provide a fair measure instead of genetic high-utility itemset mining (HUIM) for revealing the satisfied and interesting patterns. In practical applications, the database is dynamically changed when insertion/Deletion Operations are performed on databases. Several works were designed to handle the insertion process but fewer studies focused on processing the Deletion process for knowledge maintenance. In this paper, we then develop a PRE-HAUI-DEL algorithm that utilizes the pre-large concept on HAUIM for handling transaction Deletion in the dynamic databases. The pre-large concept is served as the buffer on HAUIM that reduces the number of database scans while the database is updated particularly in transaction Deletion. Two upper-bound values are also established here to reduce the unpromising candidates early which can speed up the computational cost. From the experimental results, the designed PRE-HAUI-DEL algorithm is well performed compared to the Apriori-like model in terms of runtime, memory, and scalability in dynamic databases.
Michael Vassilakopoulos - One of the best experts on this subject based on the ideXlab platform.
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the Deletion Operation in xbr trees
Panhellenic Conference on Informatics, 2012Co-Authors: George Roumelis, Michael Vassilakopoulos, Antonio CorralAbstract:In order to design a spatial index, the most important Operations are: insertion, Deletion and search. We focus on the Deletion Operation over the xBR-tree, a spatial data secondary memory structure that belongs to the Quad tree family. The algorithm of handling Deletions is presented, taking into account that the Deletion of a leaf item may cause entries Deletions from internal nodes. The well-known merging technique is applied, to retain the efficiency of the xBR-tree.
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performance evaluation of lazy Deletion methods in r trees
Geoinformatica, 2003Co-Authors: Alexandros Nanopoulos, Michael Vassilakopoulos, Yannis ManolopoulosAbstract:Motivated by the way R-trees are implemented in commercial databases systems, in this paper we examine several Deletion techniques for R-trees. In particular, in commercial systems R-tree entries are mapped onto relational tables, which implement their own concurrency protocols on top of existing table-level concurrency mechanisms. In analogy, the actual industrial implementations of B-trees do not apply the well-known merging procedure from textbooks in case of node underflows, but rather they apply the free-at-empty technique. This way, space is sacrificed for the benefit of faster Deletions and less locking Operations, whereas the search performance practically remains unaffected. In this context, we examine the efficiency of modifications to the original R-tree Deletion algorithm, which relax certain constraints of this algorithm and perform a controlled reorganization procedure according to a specified criterion. We present the modified algorithms and experimental results about the impact of these modifications on the tree quality, the execution time for the Deletion Operation and the processing time of search queries, considering several parameters. The experimental results indicate that the modified algorithms improve the efficiency of the Deletion Operation, while they do not affect the quality of the R-tree and its performance with respect to search Operations.
Antonio Corral - One of the best experts on this subject based on the ideXlab platform.
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the Deletion Operation in xbr trees
Panhellenic Conference on Informatics, 2012Co-Authors: George Roumelis, Michael Vassilakopoulos, Antonio CorralAbstract:In order to design a spatial index, the most important Operations are: insertion, Deletion and search. We focus on the Deletion Operation over the xBR-tree, a spatial data secondary memory structure that belongs to the Quad tree family. The algorithm of handling Deletions is presented, taking into account that the Deletion of a leaf item may cause entries Deletions from internal nodes. The well-known merging technique is applied, to retain the efficiency of the xBR-tree.