Merchandise Recommendation for Retail Events with Word Embedding Weighted Tf-idf and Dynamic Query Expansion
arXiv:2208.08581 · doi:10.1145/3209978.3210202
Abstract
To recommend relevant merchandises for seasonal retail events, we rely on item retrieval from marketplace inventory. With feedback to expand query scope, we discuss keyword expansion candidate selection using word embedding similarity, and an enhanced tf-idf formula for expanded words in search ranking.
The work is oral presented on the SIGIR Symposium on IR in Practice (SIRIP) 2018