Many applications have need of finding objects nearby to a specified location that contain a set of keywords.
Predictable spatial queries, consider for the object geometric include nearest neighbor retrieval and range search. From this
find out the predicate of spatial and predicate of associate texts. Academic research in this area has attention mainly on
techniques for extracting geographic knowledge from the web . At this moment in time the finest way out to such queries is
based going on IR2-tree , which showing seriously impact its efficiency. IR2-Tree is combination of R-Tree with superimposed
text signatures. For retrieving more efficient data we used the relevance feedback methods. This method makes this approach
more efficient, robust as well as reliable. In real time applications such as medical, banking et. Geographic search engine
query processing is different as it require a arrangement of text and spatial data processing techniques. In support of case,
consider all the restaurants, a nearest neighbor query would as an alternative put for the restaurant that is the closest along
with those contain steak, spaghetti, brandy all at the same time. Also motivate the by support and develop new method that is
spatial inverted. These proposed techniques best the IR2-tree in query response time.