Abstract-This paper proposed a new algorithm for answering a novel kind of nearest neighbour search, that is, continuous mutual nearest neighbour (CMNN) search. In this kind of query, by providing a set of objects O and a query object q, CMNN continuously returns the set of objects from O, which is among the k 1 nearest neighbours of q; meanwhile, q is one of their k 2 nearest neighbours. CMNN queries are important in many applications such as decision making, pattern recognition and although it is useful in service providing systems, such as police patrol, taxi drivers, mobile car repairs and so forth. In this paper, we have proposed the first work for handling CMNN queries efficiently, without any assumption on object movements. The most important feature of this work is incremental evaluation and scalability. Utilizing an incremental evaluation technique led to a significant decrease in processing time.Index Terms-Moving objects, nearest neighbor, query processing, spatio-temporal.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.