Comparative Study of Lexical and Semantic Approaches in Closed-domain Product Search
Francisco Igor de Lima Mendes, M.C. Silva, André Luíz Firmino Alves, Eniedson Fabiano Pereira da Silva Júnior, Mateus Queiroz Cunha, Cláudio de Souza Baptista · 2025
One of the key challenges in information retrieval from closed-domain documents is the prevalence of technical and abbreviated terms specific to the domain. This scenario often hinders users from effectively searching for relevant information, even when available. The presentation and structure of product information are crucial for the reliability of a product search system from a user perspective. Lexical and semantic search methods are commonly employed in such applications. In this work, we evaluate the trade-offs of these techniques across two datasets with distinct domains and structures: electronic invoices and a governmental product catalog. Our results suggest that lexical search algorithms, such as BM25, tend to retrieve more relevant products faster, whereas semantic search methods rank the relevant documents more effectively.