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In this paper, we develop a neural multi-document summarization model, named MuD2H (refers to Multi-Document to Headline) to generate an attractive and customized headline from a set of product descriptions. To the best of our knowledge, no one has used a technique for multi-document summarization to generate headlines in the past. Therefore, multi-document headline generation can be considered new problem setting. Our model implements a two-stage architecture, including an extractive stage anddoi:10.1109/access.2022.3157287 fatcat:ad5c5huf3vhpzb4xa2z54fjtja