TwiCS: Twitter Stream Entity Mention Detection (Extended Abstract)
Satadisha Saha Bhowmick, Eduard Dragut, Weiyi Meng · 2022 IEEE 38th International Conference on Data Engineering (ICDE) · 2022
In this paper, we propose a system TwiCS for Entity Mention Detection (EMD) and Entity Detection (ED) in streaming environments. TwiCS employs a computationally light two-phase process: (1) exploit simple (low computation) syntactic cues to suggest Entity Mention (EM) candidates and (2) use occurrence mining to classify candidates according to their likelihood of being true EMs. Our experiments show that on average TwiCS improves effectiveness by 14.6%, while achieving at least 2.64 times higher throughput, when compared to several state-of-the-art systems.