An Efficient Nearest Neighbor Searching Method

Conservative spatial queries, such as range search and nearest neighbor reclamation, involves only conditions on objects’ numerical properties. Today, many modern applications call for novel forms of queries that aim to find objects 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 “steak, spaghetti, brandy” all at the same time. Currently the best solution to such queries is based on the InformationRetrieval2-tree, which has a few deficiencies that seriously impact its efficiency. Motivated by this, there is a development of a new access method called the spatial inverted index that extends the conventional inverted index to cope with multidimensional data, and comes with algorithms that can answer nearest neighbor queries with keywords in real time. As verified by experiments, the proposed techniques outperform the InformationRetrieval2-tree in query response time significantly, often by a factor of orders of magnitude