Facilitating Twitter data analytics: Platform, language and functionality
作者： Ke Tao , Claudia Hauff , Geert-Jan Houben , Fabian Abel , Guido Wachsmuth
DOI: 10.1109/BIGDATA.2014.7004259
关键词: Social web 、 Set (abstract data type) 、 Computer science 、 Analytics 、 Data analysis 、 Workflow 、 Use case 、 Data collection 、 World Wide Web 、 Interface (Java)
摘要: Conducting analytics over data generated by Social Web portals such as Twitter is challenging, due to the volume, variety and velocity of data. Commonly, adhoc pipelines are used that solve a particular use case. In this paper, we generalize across range typical Twitter-data cases determine set common characteristics. Based on investigation, present our Analytical Platform (TAP), generic platform for conducting analytical tasks with The provides domain-specific Analysis Language (TAL) interface its functionality stack. TAL includes analysis tools ranging from collection semantic enrichment, machine learning. With these tools, it becomes possible create customize workflows in build applications make results. We showcase applicability building Twinder-a search engine streams.
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