English

Merchandise Recommendation for Retail Events with Word Embedding Weighted Tf-idf and Dynamic Query Expansion

Information Retrieval 2022-08-19 v1 Machine Learning

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.

Keywords

Cite

@article{arxiv.2208.08581,
  title  = {Merchandise Recommendation for Retail Events with Word Embedding Weighted Tf-idf and Dynamic Query Expansion},
  author = {Ted Tao Yuan and Zezhong Zhang},
  journal= {arXiv preprint arXiv:2208.08581},
  year   = {2022}
}

Comments

The work is oral presented on the SIGIR Symposium on IR in Practice (SIRIP) 2018