SYSTEM, METHOD AND APPARATUS FOR AUTOMATIC TOPIC RELEVANT CONTENT FILTERING FROM SOCIAL MEDIA TEXT STREAMS USING WEAK SUPERVISION

摘要

Presented are a system, method, and apparatus for automatic topic relevant content filtering from social media text streams using weak supervision. A computing device utilizes heuristic rules allowing topic filtering and a data stream data chunk identifier. A plurality of messages are transmitted as streaming message data from a social media network in real-time. The messages are split into a plurality of data stream data chunks according to the data stream data chunk identifier. A rule-based labeled data set L₀ is built from one or more data instances in the first stream data chunk. An initial classifier is built based upon features of L₀. The initial classifier is applied to a next data stream data chunk to build a labeled data set L₁. A subset of representative instances S₁ is selected from labeled data set L₁. A first representative classifier C₁ is constructed from representative instance S₁.