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A Multi-task Learning Approach for Improving Product Title Compression with User Search Log Data
[article]
2018
arXiv
pre-print
It is a challenging and practical research problem to obtain effective compression of lengthy product titles for E-commerce. This is particularly important as more and more users browse mobile E-commerce apps and more merchants make the original product titles redundant and lengthy for Search Engine Optimization. Traditional text summarization approaches often require a large amount of preprocessing costs and do not capture the important issue of conversion rate in E-commerce. This paper
arXiv:1801.01725v1
fatcat:upfviymp6rhnxepfna7quuwa2m