Fast keyword searching using SI-Index in Data Warehouse
Abstract
In data warehouse system we have large number of data. To search In Huge amount of Data .we need to go through the fast nearest neighbor search that we follow some traditional methods like range calculation and nearest neighbors search but it purely depend upon conditions that are given to database. For example a nearest neighbor query search restaurant that is the closest among many restaurants within a particular area, whose menu contain required food keyword with respect to query. The problems of the nearest neighbor search on spatial data and keyword search on text data have been studied separately. Existing solution to queries is based on IR2 -Tree (Information Retrieval R-Tree), but it has a few deficiencies that it requires more time to process the query and fails to give real time answers. To overcome these problems, we introduced the Inverted Index that is called as spatial inverted index. That have different level of organizing the Big data for Minimizing search . It have gap filling technique and z-curve values due to this we can adjust the space in the index table so data object will be adjusted then the elements will have range to calculate or search with in the data warehouse.
Keywords: Nearest Neighbor; Keyword; SI-Index; R-Tree
Keywords: Nearest Neighbor; Keyword; SI-Index; R-Tree
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PDFCopyright (c) 2015 Motati.Rama Mohan Reddy, D. Kumar
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