Crawling Hidden Objects with KNN Queries - 2016 PROJECT TITLE: Crawling Hidden Objects with KNN Queries - 2016 ABSTRACT: With rapidly growing popularity, Location Primarily based Services (LBS), e.g., Google Maps, Yahoo Native, WeChat, FourSquare, etc., started offering web-primarily based search features that resemble a kNN question interface. Specifically, for a user-specified query location q, these websites extract from the objects in their backend database the high-k nearest neighbors to q and come these k objects to the user through the.Net interface. Here k is usually a tiny value like 50 or 100. For example, McDonald [one] returns the prime twenty five nearest restaurants for a user-specified location through its locations search webpage. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest Detecting Node Failures in Mobile Wireless Networks A Probabilistic Approach - 2016 Bilevel Feature Extraction-Based Text Mining for Fault Diagnosis of Railway Systems - 2016
