Abstract

Abstract:

Conventionalspatial queries, such as range search and nearest neighbor retrieval, involveonly conditions on objects geometric properties. Today, many modernapplications call for novel forms of queries that aim to find objectssatisfying both a spatial predicate, and a predicate on their associated texts.For example, instead of considering all the restaurants, a nearest neighborquery would instead ask for the restaurant that is the closest among thosewhose menus contain “steak, spaghetti, brandy” all at the same time. A searchengine is able to efficiently support novel forms of spatial queries which areintegrated with keyword explore. The accessible solutions to such queries alsoacquire prohibitive space consumption or are unable to give real time answers.As today’s need is smart search from search engine not just what they query butrelevant to query and similar to that query and where they actually find thatproduct, place or person in real world. To provide such smart search resultsfast nearest neighbor search with keywords technique by using spatial invertedindex (SI-index) has been proposed by researchers. This technique has greatefficiency to provide results but processes huge data to fulfill queries. Toovercome huge data pre-processing, proposed algorithm reduces no of objectsprocessed by this technique to minimize the memory and processing cost.Proposed technique uses limits to fetch limited objects from the dataset ordatabase.

Keywords: Superimposed Coding, nearest neighbor search,keyword search, spatial index, FNNSK, AFNNSK.