Joint Optimization of User-desired Content in Multi-document Summaries by Learning from User Feedback

@inproceedings{Avinesh2017JointOO,
  title={Joint Optimization of User-desired Content in Multi-document Summaries by Learning from User Feedback},
  author={P. V. S. Avinesh and Christian M. Meyer},
  booktitle={ACL},
  year={2017}
}
In this paper, we propose an extractive multi-document summarization (MDS) system using joint optimization and active learning for content selection grounded in user feedback. Our method interactively obtains user feedback to gradually improve the results of a state-of-the-art integer linear programming (ILP) framework for MDS. Our methods complement fully automatic methods in producing highquality summaries with a minimum number of iterations and feedbacks. We conduct multiple simulation-based… CONTINUE READING

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