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Answer Summarization for Technical Queries: Benchmark and New Approach

Chengran Yang, Bowen Xu, Ferdian Thung, Yucen Shi, Ting Zhang, Zhou Yang, Xin Zhou, Jieke Shi, Junda He, DongGyun Han, David Lo

Abstract

Prior studies have demonstrated that approaches to generate an answer summary for a given technical query in Software Question and Answer (SQA) sites are desired. We find that existing approaches are assessed solely through user studies. Hence, a new user study needs to be performed every time a new approach is introduced; this is time-consuming, slows down the development of the new approach, and results from different user studies may not be comparable to each other. There is a need for a benchmark with ground truth summaries as a complement assessment through user studies. Unfortunately, such a benchmark is non-existent for answer summarization for technical queries from SQA sites.

BibTeX
@inproceedings{Yang-al:ASE22,
  author    = {Chengran Yang and
               Bowen Xu and
               Ferdian Thung and
               Yucen Shi and
               Ting Zhang and
               Zhou Yang and
               Xin Zhou and
               Jieke Shi and
               Junda He and
               DongGyun Han and
               David Lo},
  title     = {Answer Summarization for Technical Queries: Benchmark and New Approach},
  booktitle = {ASE},
  pages     = {8:1--8:13},
  publisher = {{ACM}},
  year      = {2022},
}

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