NEAREST NEIGHBOUR EXPANSION USING KEYWORD COVER SEARCH

Abstract

Spatial databases are stores the information about the spatial objects which are associated with the keywords to show the information such as its business/services/features. Very important problem known as closest keywords search is to query objects, called keyword cover. In nearest keyword search, it covers a set of query keywords and minimum distance between objects. From last few years, keyword rating increases its availability and importance in object evaluation for the decision making. This is the main reason for developing this new algorithm called Best keyword cover which is considers inter distance as well as the rating provided by the customers through the online business review sites. Closest keyword searchalgorithm combines the objects from various query keywords to a generate candidate keyword cover. Two algorithms Base-line algorithm and keyword nearest-neighborexpansion algorithms are used to finding best keyword cover. The performance of the closest keyword algorithm drops dramatically, when the number of query keyword increases. The solution of this problem of the existing algorithm, this work proposes generic version called keyword nearest neighbor expansion which reduces the resulted candidate key-word covers.