ISISTAN   23985
INSTITUTO SUPERIOR DE INGENIERIA DEL SOFTWARE
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
A Programming Interface and Platform Support for Developing Recommendation Algorithms on Large-scale Social Networks
Autor/es:
ALEJANDRO CORBELLINI; CRISTIAN MATEOS; DANIELA GODOY; ALEJANDRO ZUNINO; SILVIA SCHIAFFINO
Lugar:
Santiago de Chile
Reunión:
Congreso; 20th International Conference on Collaboration and Technology (CRIWG 2014) - LECTURE NOTES IN COMPUTER SCIENCE; 2014
Resumen:
Friend and followee recommendation algorithms in large-scale social networks such as Facebook or Twitter usually require and efficient exploration of huge and exponentially growing user graphs. In current solutions such as distributed graph-specific databases or frameworks for parallelizing graph algorithms, the burden of dealing with distribution and parallel concerns falls on algorithm developers. In this paper, a simple yet powerful programming interface (API) to implement graph traversal algorithms is presented. This interface facades a three-layer architecture comprising an application layer, a platform layer, and a storage layer, comprising decisions about the mentioned concerns. A case study on implementing a followee recommendation algorithm for Twitter using the API and the proposed middleware is described. This case study not only illustrates the simplicity offered by the API for developing algorithms even with complex navigational patterns, but also how different aspects of the distributed solutions can be treated and experimented without altering the algorithm code. Experiments evaluating the performance of different job scheduling strategies illustrate the flexibility or our approach.