Modified Query Expansion Through Generative Adversarial Networks for Information Extraction in E-Commerce. (arXiv:2301.00036v1 [cs.LG])

This work addresses an alternative approach for query expansion (QE) using a
generative adversarial network (GAN) to enhance the effectiveness of
information search in e-commerce. We propose a modified QE conditional GAN
(mQE-CGAN) framework, which resolves keywords by expanding the query with a
synthetically generated query that proposes semantic information from text
input. We train a sequence-to-sequence transformer model as the generator to
produce keywords and use a recurrent neural network model as the discriminator
to classify an adversarial output …

addresses adversarial commerce e-commerce framework gan generated generative generative adversarial networks information network networks query search work