GeoTeGra: A System for the Creation of Knowledge Graph Based on Social Network Data with Geographical and Temporal Information.

ASONAM '18: International Conference on Advances in Social Networks Analysis and Mining Barcelona Spain August, 2018(2018)

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摘要
During the last decade, a variety of social networks and applications has been developed, providing to the users a set of potential functionalities. Thanks to these functionalities, they have become vital part of the daily life of many people. As a result, a great volume of data has been created. Due to the different nature of the functionalities, datasets of different nature and schema are created. This paper introduces GeoTeGra, a system that targets to reveal non-obvious knowledge by connecting datasets that derive from multiple heterogeneous sources. GeoTeGra is a scalable framework to compare different machine learning algorithms in terms of scalability and effectiveness, finding semantic similarities between entities. Our system is based on a distributed storage and parallel map-reduce manipulation for the fast retrieval of information from multi-class feature representations.
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关键词
GeoTeGra,knowledge graph,social network data,potential functionalities,datasets,nonobvious knowledge,multiple heterogeneous sources,scalable framework,distributed storage,parallel map-reduce manipulation,geographical information,temporal information,multiclass feature representations,machine learning algorithms
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