LinkSO: A Benchmark for Learning to Retrieve Similar Question-Answer Pairs on Software Development Forums
- Xueqing Liu ,
- Chi Wang ,
- Yue Leng ,
- Chengxiang Zhai
ESEC/FSE Workshop on NLP for Software Engineering (NL4SE'18) |
We present LinkSO, a dataset for learning to rank similar questions on Stack Overflow. Stack Overflow contains a massive amount of crowd-sourced question links of high quality, which provides a great opportunity for evaluating retrieval algorithms for community-based question answer (cQA) archives and for learning to retrieve similar questions. However, due to the existence of missing links, one question is whether question links can be readily used as the relevance judgment for evaluation. We study this question by measuring the closeness between question links and the relevance judgment, and we find their agreement rates range from 80% to 88%. We conduct an empirical study that evaluates existing retrieval models’ performance on LinkSO. While existing work focuses on non-learning approaches, our preliminary exploration that assembles simple learning models shows great potential for further improving the retrieval performance with machine learning.