Given a point p and a set of points S, the kNN operation finds the k closest points to p in S. It is a compu-tational intensive task with a large range of applications such as knowledge discovery or data mining. However, as the volume and the dimension of data increase, only distributed approaches can perform such costly operation in a...
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March 4, 2015 (v1)Conference paperUploaded on: March 25, 2023
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July 7, 2015 (v1)Journal article
In many social networks, people interact based on their interests. Community detection algorithms are then useful to reveal the sub-structures of a network and in particular interest groups. Identifying these users' communities and the interests that bind them can help us assist their life-cycle. Certain kinds of online communities such as...
Uploaded on: February 28, 2023 -
August 17, 2014 (v1)Conference paper
In many social networks, people interact based on their interests. Community detection algorithms are then useful to reveal the sub-structures of a network and help us find interest groups. Identifying these social communities can bring benefit to understanding and predicting users behaviors. However, for some kind of online community sites...
Uploaded on: February 28, 2023 -
2016 (v1)Journal article
Given a point p and a set of points S, the kNN operation finds the k closest points to p in S. It is a computational intensive task with a large range of applications such as knowledge discovery or data mining. However, as the volume and the dimension of data increase, only distributed approaches can perform such costly operation in a...
Uploaded on: February 28, 2023 -
2018 (v1)Journal article
Presents corrections to the paper, "K nearest neighbour joins for big data on MapReduce: A theoretical and experimental analysis," (Song, G., et al), IEEE Trans. Knowl. Data Eng., vol. 28, no. 9, pp. 2376–2392, Sep. 2016.
Uploaded on: December 4, 2022 -
November 13, 2013 (v1)Conference paper
More and more Internet companies rely on large scale data analysis as part of their core services for tasks such as log analysis, feature extraction or data filtering. Map-Reduce, through its Hadoop implementation, has proved to be an efficient model for dealing with such data. One important challenge when performing such analysis is to predict...
Uploaded on: October 11, 2023 -
November 13, 2013 (v1)Conference paper
More and more Internet companies rely on large scale data analysis as part of their core services for tasks such as log analysis, feature extraction or data filtering. Map-Reduce, through its Hadoop implementation, has proved to be an efficient model for dealing with such data. One important challenge when performing such analysis is to predict...
Uploaded on: December 3, 2022