Best Keyword Cover Search Using Distance and Rating

Abstract

Spatial databases are stores the information about
the spatial objects which are associated with the keywords to
indicate the information such as its business/services/fea-tures.
Very important problem known as closest keywords search
is to query objects, called keyword cover. In closest 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 search
algorithm combines the objects from different query keywords
to generate candidate keyword covers. Baseline algorithm and
keyword nearest neighbors expansion algorithms are used to
find the best keyword cover. The performance of the closest
keyword algorithm drops dramatically, when the number of
query keyword increases. To solve this problem of the existing
algorithm, this work proposes generic version called keyword
nearest neighbor expansion which reduces the resulted candidate
keyword covers.