NEAREST KEYWORD SEARCH BY MEASURING SEMANTIC SIMILARITY
Harsha Aravind M · International journal of scientific research · 2015
Spatial queries, such as range search and nearest neighbor retrieval, involve only conditions on objects geometric properties. A spatial database manages multidimensional objects(such as points, rectangles, etc.), and provides fast access to those objects based on different selection criteria. Now-a-days many applications call a new form of queries to find the objects that satisfying both a spatial predicate, and a predicate on their associated texts. For example, instead of considering all the restaurants, a nearest neighbor query would instead ask for the restaurant that is the closest among those whose menus contain the specified keywords all at the same time.Concept of IR2-tree and spatial inverted index is used in the existing system for providing best solution for finding nearest neighbor and also it is a simple web application that stores a collection of documents in Database. This method has few deficiencies. So proposed a new technique which includes extracting synonyms and measuring semantic similarity to improve the query results.