Putting the User in the Loop: Interactive Maximal Marginal Relevance for Query-Focused Summarization
Jimmy Lin, Nitin Madnani, Bonnie Jean Dorr · 2010
This work represents an initial attempt to move beyond “single-shot ” summarization to interactive summarization. We present an extension to the classic Maximal Marginal Relevance (MMR) algorithm that places a user “in the loop ” to assist in candidate selection. Experiments in the complex interactive Question Answering (ciQA) task at TREC 2007 show that interactively-constructed responses are significantly higher in quality than automatically-generated ones. This novel algorithm provides a starting point for future work on interactive summarization. 1