Search Results - ((((text processing) OR (good processing))) OR (((query processing) OR (data processing))))

A systematic literature review of skyline query processing over data stream by Mohamud, Mudathir Ahmed, Ibrahim, Hamidah, Sidi, Fatimah, Rum, Siti Nurulain Mohd, Dzolkhifli, Zarina Binti, Xiaowei, Zhang, Lawal, Ma’aruf Mohammed

“…Although an abundance of skyline query processing techniques have been proposed, there is a lack of a Systematic Literature Review (SLR) on current research works pertinent to skyline query processing over data stream. …”
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Efficient top-k continuous query processing over sliding window model (SWM) method on uncertain data stream by Wahab, Raja Azhan Syah Raja, Rum, Siti Nurulain Mohd, Ibrahim, Hamidah, Ishak, Iskandar

“…Query processing using the Uncertain Data Stream (UDS) can be complex in many technological scenarios due to inconsistencies, unclear information, and interpretation latency. …”
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Keyword query processing interface model of ontological natural language manipulation by Hasany, Syed Muhammad Noman

“…The process of manipulating both type of natural language (NL) queries are supported by Ontologies. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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Efficient management of Top-k queries over Uncertain Data Streams with dynamic Sliding Window Model by Raja Wahab, Raja Azhan Syah

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Collaborative caching for distributed mobile database query processing by Elfaki, Mohamed Ahmed, Ibrahim, Hamidah, Mamat, Ali, Othman, Mohamed

“…Since our approach deals with continuous query, we propose a framework for improving the process of continuous query mechanism that caches and shares the query’s result among the nodes within the same cluster or with external database (neighbors cluster or main data server).…”
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JQPro: Join query processing in a distributed system for Big RDF data using the hash-merge join technique by Nahla Mohammed Elzein, Mazlina Abdul Majid, Ibrahim Abaker Targio Hashem, Ashraf Osman Ibrahim Elsayed, Anas W. Abulfaraj, Faisal Binzagr

“…To address this complication, we introduce a join query processing model for big RDF data, called JQPro. …”
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An efficient approach for processing skyline queries in incomplete multidimensional database by Alwan, Ali Amer, Ibrahim, Hamidah, Udzir, Nur Izura, Sidi, Fatima

“…In recent years, there has been great attention given to skyline queries that incorporate and provide more flexible query operators that return data items (skylines) which are not being dominated by other data items in all dimensions (attributes) of the database. …”
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Accuracy of queries for storage space optimisation in green data centre by Rabatul Aduni, Sulaiman

“…Another table in this situation is referred to the proxy map table. The query is needed in the retrieval process. But, it needs to make sure that the query is more simple and able to retrieve the data. …”
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loT database for non structured data type by LOH, YI LING

“…With FastTextProcessor, users can query data directly from the file directory, accelerate the data extraction process. …”
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Measuring transaction performance based on storage approaches of Native XML database by Marjani, Mohsen, Nasaruddin, Fariza Hanum, Gani, Abdullah, Shamshirband, Shahaboddin

“…The results of the evaluation show that the schema-based storage strategy: performs 3.5 times faster than the other two storage techniques in data insertion; shows very good performance in query processing on small and large datasets; performs 10.33 times faster than text-based, and 7.5 times faster than model-based storage techniques in query processing of large datasets.…”
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Uncertain data: Forms, Semantics, Processing Queries / Trieu Minh Nhut Le, Thanh Ngoc Thi Nguyen, and Dung Hoang Thi Ngoc by Trieu, Minh Nhut Le, Thanh, Ngoc Thi Nguyen, Dung, Hoang Thi Ng

“…In this paper, we first review and classify types of uncertain data in specific scenario. Secondly, some cases of queries processing to demonstrate the semantics on uncertain data are analysed based on their answers. …”
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An efficient skyline model for processing multiple continuous skyline queries over uncertain data stream by Ahmed Mohamud, Mudathir, Ibrahim, Hamidah, Sidi, Fatimah, Mohd Rum, Siti Nurulain

“…Thus, it would be imprudent to process the same portion of the data stream and the same objects repeatedly in order to satisfy these queries. …”
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SQL queries optimization for UiTM student academic system using Oracle hints / Mohd Junaidi Johari by Johari, Mohd Junaidi

“…Query optimization is the most critical phase in query processing. …”
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Increasing the performance of iceberg query through summary tables by Gohar Rahman, Wajid Ali, Mehmood Ahmed, Hassan Jamil Sayed, Mohammad A. Saleh

“…However the processing devices have limited memories, so the efficient processing of iceberg queries is a challenging problem for most of the researchers. …”
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Enhance efficiency of answering XML keyword query using incompact structure of MCCTree by Sazaly, Ummu Sulaim

“…This study identifies the effective processes needed in producing XML query result using MCLCA notion and without compacting it. …”
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IDSA: an efficient algorithm for skyline queries computation on dynamic and incomplete data with changing states by Gulzar, Yonis, Alwan, Ali Amer, Ibrahim, Hamidah, Turaev, Sherzod, Wani, Sharyar, Soomo, Arjumand Bano, Hamid, Yasir

“…Data incompleteness causes several challenges on skyline queries such as losing the transitivity property of the skyline technique and the test dominance process between tuples being cyclic. …”
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CSQUiD: an index and non-probability framework for constrained skyline query processing over uncertain data by Lawal, Ma'aruf Mohammed, Ibrahim, Hamidah, Mohd Sani, Nor Fazlida, Yaakob, Razali, Alwan, Ali A.

“…Therefore, this work introduces an index, non-probability framework named Constrained Skyline Query processing on Uncertain Data (CSQUiD) aiming at reducing the computational time in processing constrained skyline queries over uncertain high-dimensional data. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian by Talebian, Seyed Hamid

“…Since analytical queries are complex and take a long time to be processed under normal circumstance, there is a need for a strategy to improve the speed of such queries. …”
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Dominance relationship-based skyline query framework over dynamic and incomplete database by Dehaki, Ghazaleh Babanejad

“…However, computing the skylines over the entire database after changes are made is inefficient as not all the data items are affected by the changes. In tackling the above stated issues, we propose a solution, named DyIn-Skyline, which consists of three main phases, namely: Phase I – processing skyline queries over the initial incomplete database, Phase II – processing skyline queries over a dynamic and incomplete database, in which the changing state of the database is due to a data manipulation operation(s) (insert, delete or update a data item(s)), and Phase III – processing skyline queries over a dynamic and incomplete database, in which the changing state of the database is due to a data definition operation(s) (add or remove a dimension(s)). …”
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