Efficient Processing of k Nearest Neighbor Joins using MapReduce

k nearest neighbor join (kNN join), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operation widely adopted by many data mining applications. As a combination of the k nearest neighbor query and the join operation, kNN join is an expensive operation. Given the increasing volume of data, it is difficult to perform a kNN join on a centralized machine efficiently. In this paper, we investigate how to perform kNN join using MapReduce which is a well-accepted framework for data-intensive applications over clusters of computers. In brief, the mappers cluster objects into groups; the reducers perform the kNN join on each group of objects separately. We design an effective mapping mechanism that exploits pruning rules for distance filtering, and hence reduces both the shuffling and computational costs. To reduce the shuffling cost, we propose two approximate algorithms to minimize the number of replicas. Extensive experiments on our in-house cluster demonstrate that our proposed methods are efficient, robust and scalable.Comment: VLDB201

A Framework for Recommending Multimedia Cultural Visiting Paths

In this work, we present a general framework for Cultural Heritage applications able to uniformly manage heterogeneous multimedia data coming from several web repositories and to provide context- Aware recommendation services in order to generate dynamic multimedia visiting paths useful for the users during the exploration of different kinds of cultural sites. A specific application of our system within the cultural heritage domain is proposed together with some experimental results

DEVELOPING AUGMENTED REALITY PLACES OF INTEREST APPLICATION OF UNIVERSITI TEKNOLOGI PETRONAS (UTP)

This report is a preliminary step onto developing Augmented Reality places of interest application of Universiti Teknologi PETRONAS (UTP). As of 2007, UTP holds the recognition with the prestigious Aga Khan Award for Architecture in Malaysia. Having said that, domestic as well as international visitors annually visit UTP to apprehend the unique and award winning design of its campus. But the current problem which persists for visitors is the need for a guide and lack of a general source of information regarding the university's campus during their visits. With such problem in place, it is therefore extremely pivotal to have an Augmented Reality mobile application that will help them find significant places within the campus itself. This allows them to explore the entire university through their mobile phones and have useful information at the touch of their fingertips. The project will involve several phases; firstly the construction of the Augmented Reality application itself, followed by the analysis and design of the rules for the Augmented Reality application, the development of the Augmented Reality application, further testing and finally the implementation of the Augmented Reality application. These implementations, using the Rapid Application Development methodology with the Prototyping approach was further refmed through the research and studies as well as feedback obtained from colleagues until it appropriately meets the objectives