A Distributed Platform to Ease the Development of Recommendation Algorithms on Large-Scale Graphs

Corbellini, Alejandro

A Distributed Platform to Ease the Development of Recommendation Algorithms on Large-Scale Graphs

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Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Doctoral Consortium. Pages 4353-4353.

Abstract

The creation of novel recommendation algorithms for social networks is currently struggling with the volume of available data originating in such environments. Given that social networks can be modeled as graphs, a distributed graph-oriented support to exploit the computing capabilities of clusters arises as a necessity. In this thesis, a platform for graph storage and processing named Graphly is proposed along with GraphRec, an API for easy specification of recommendation algorithms. Graphly and GraphRec hide distributed programming concerns from the user while still allowing fine-tuning of the remote execution. For example, users may customize an algorithm execution using job distribution strategies, without modifying the original code. GraphRec also simplifies the design of graph-based recommender systems by implementing well-known algorithms as “primitives” that can be reused.

Alejandro Corbellini. 2015. A Distributed Platform to Ease the Development of Recommendation Algorithms on Large-Scale Graphs. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 4353–4353. https://ijcai.org/proceedings/2015/624

@inproceedings{ijcai2015p624,
  title     = {A Distributed Platform to Ease the Development of Recommendation Algorithms on Large-Scale Graphs},
  author    = {Corbellini, Alejandro},
  booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-15}},
  publisher = {International Joint Conferences on Artificial Intelligence},
  editor    = {Qiang Yang and Michael Wooldridge},
  pages     = {4353--4353},
  year      = {2015},
  month     = {7},
  note      = {Doctoral Consortium},
  url       = {https://ijcai.org/proceedings/2015/624},
}

TY  - CPAPER
TI  - A Distributed Platform to Ease the Development of Recommendation Algorithms on Large-Scale Graphs
AU  - Corbellini, Alejandro
T2  - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15
PB  - International Joint Conferences on Artificial Intelligence
PY  - 2015
SP  - 4353
EP  - 4353
UR  - https://ijcai.org/proceedings/2015/624
ER  -