MicroFilter: Scalable Real-Time Filtering Of Micro-blogging Content
2013
Abstract. Microblogging systems have become a major trend over the
Web. After only 7 years of existence, Twitter for instance claims more
than 500 million users with more than 350 billion delivered update each
day. As a consequence the user must today manage possibly extremely
large feeds, resulting in poor data readability and loss of valuable infor-
mation and the system must face a huge network load. In this demon-
stration, we present and illustrate the features of MicroFilter (MF in the
the following), an inverted list-based filtering engine that nicely extends
existing centralized microblogging systems by adding a real-time filtering
feature. The demonstration proposed illustrates how the user experience
is improved, the impact on the traffic for the overall system, and how the
characteristics of microblogs drove the design of the indexing structures.
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