Feature-Specific Named Entity Recognition in Software Development Social Content
Ning Li, Liwei Zheng, Ying Wang, Bin Wang · 2019
Software development social networking sites, such as Stack Overflow or CSDN, contain rich information on software functions. The SFF(Software Function Feature)-specific named entities could be mined from this information. And furthermore, the usage patterns of entities and issues-solutions could also be mined based on the recognition of SFF-specific named entities. However, the existing workes on named entity recognition mainly focuses on the medicine filed and news filed. In the field of software engineering, there is little research on software named entity recognition. In fact, the contents of Software Development Social Networking sites are always freeform texts, which is composed of source code, link, abbreviation and Chinese or English words. It brings some difficulties to the SFF-specific named entity recognition. So in this paper, we gives an approach for SFF-specific named entity recognition with the BI-LSTM(Bidirectional Long Short-Term Memory) model and word embedding technique. A preliminary empirical evaluation demonstrates that our approach is effective to recognize SFFspecific named entities in software development social networking sites contents.