TPDR: A Novel Two-Step Transformer-based Product and Class Description
  Match and Retrieval Method
Washington Cunha Celso França Leonardo Rocha Marcos André Gonçalves
There is a niche of companies responsible for intermediating the purchase of
large batches of varied products for other companies, for which the main
challenge is to perform product description standardization, i.e., matching an
item described by a client with a product described in a catalog. The problem
is complex since the client's product description may be: (1) potentially
noisy; (2) short and uninformative (e.g., missing information about model and
size); and (3) cross-language. In this paper, we formalize this problem as a
ranking task: given an initial client product specification (query), return the
most appropriate standardized descriptions (response). In this paper, we
propose TPDR, a two-step Transformer-based Product and Class Description
Retrieval method that is able to explore the semantic correspondence between IS
and SD, by exploiting attention mechanisms and contrastive learning. First,
TPDR employs the transformers as two encoders sharing the embedding vector
space: one for encoding the IS and another for the SD, in which corresponding
pairs (IS, SD) must be close in the vector space. Closeness is further enforced
by a contrastive learning mechanism leveraging a specialized loss function.
TPDR also exploits a (second) re-ranking step based on syntactic features that
are very important for the exact matching (model, dimension) of certain
products that may have been neglected by the transformers. To evaluate our
proposal, we consider 11 datasets from a real company, covering different
application contexts. Our solution was able to retrieve the correct
standardized product before the 5th ranking position in 71% of the cases and
its correct category in the first position in 80% of the situations. Moreover,
the effectiveness gains over purely syntactic or semantic baselines reach up to
3.7 times, solving cases that none of the approaches in isolation can do by
themselves.