Paper: Resolving Entity Morphs in Censored Data

ACL ID P13-1107
Title Resolving Entity Morphs in Censored Data
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2013

In some societies, internet users have to create information morphs (e.g. ?Peace West King? to refer to ?Bo Xilai?) to avoid active censorship or achieve other com- munication goals. In this paper we aim to solve a new problem of resolving en- tity morphs to their real targets. We ex- ploit temporal constraints to collect cross- source comparable corpora relevant to any given morph query and identify target can- didates. Then we propose various novel similarity measurements including surface features, meta-path based semantic fea- tures and social correlation features and combine them in a learning-to-rank frame- work. Experimental results on Chinese Sina Weibo data demonstrate that our ap- proach is promising and significantly out- performs baseline methods1.