[Praveena*, 5(5): May, 2016] ISSN: 2277-9655 Impact Factor: 3.785 http: // www.ijesrt.com © International Journal of Engineering Sciences & Research Technology [213] IJESRT INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY FAST NEAREST NEIGHBOUR SEARCH WITHIN ARBITRARY SUBSPACES H.Praveena*, M.Saravanan M.Tech II Year Department of Information Technology, Ganadipathy Tulsi’s Jain Engineering College, Kaniyambadi, Vellore-632102. Associate Professor Department of Information Technology, Ganadipathy Tulsi’s Jain Engineering College, Kaniyambadi, Vellore-632102 DOI: 10.5281/zenodo.51024 ABSTRACT A spatial database is a database that is optimized to store and query data that represents objects defined in a geometric space. Many spatial queries involve only conditions on objects’ geometric properties for search but the case is modern applications are in need of queries that aim to find objects satisfying both a spatial predicate, and a predicate on their associated texts. There are some straight forward approach which first deals with spatial predicate and then on the non-spatial predicate as a process of reduction. But these approaches are not good with complex queries. So in this project propose an inverted index called as spatial inverted index (SI-index) which converts the multi-dimensional data objects into ids this reduces the required space for processing which is the main disadvantage of the existing systems. This project perform location querying in more arbitrary subspaces for example searching hospital with more information’s like heart specialist and check rooms availability etc. KEYWORD: spatial inverted index (SI-index), geometric properties. INTRODUCTION A spatial database is database. The importance of spatial databases is reflected by the conveniene of modeling entities of reality in a geo-metric manner. For example, locations of restaurants, hotels, hospitals and soon are of represented as points in a map, while larger extents such as parks, lakes, and scapes often as a combination of rectangles. Many functionalities of a spatial database are useful in various ways in specific contexts. For instance, in a geography information system, range search can be deployed to find all restaurant‘s in a certain area, while nearest neighbor retrieval can discover the restaurant closest to a given address.Conventionally, queries focus on objects geometric properties only, such as whether a point is in a rectangle, or how closet points are from each other. We have seen some modern applications that call for the ability to select objects based on both of their geometric coordinates and their associated texts. For example, it would be fairly useful if a search engine can be used to find the nearest hospital that offers “rooms, beds”all at the sametime. PROBLEM DEFINITIONS Let P be a set of multidimensional points. A sourgoalisto combine keyword search with the existing location-finding services on facilities such as hospitals, restaurants, hotels, etc., we will focus on dimensionality, but our technique can be extended to arbitrary dimensionalities with no technical obstacle. We will assume that the points in P have integer coordinates, such that each coordinate ranges in ½0;t, where t is a large integer.This is not as restrictive as it may seem, because even if one would like to insist on real-valued coordinates, the set of different coordinates represent able under a space limit is still finite and enumerable; therefore, we could as well convert everything to integers with proper scaling. As with, each point p2 P is associated with a set of words, which is denoted as Wp and termed the document of p. For example, if p stands for a restaurant, Wp can be its menu, or if p is a hotel, Wp can be the description of its services and facilities, or if p is a hospital, Wp can be the list of its outpatient specialities. It is clear that Wp may potentially contain numerous words.