2018/07/05 by Aliasgar Kutiyanawala, Kutiyanawala, Aliasgar, Prateek Verma +4
Computer Science · #Advanced Text Analysis Techniques #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Semantic Web and Ontologies #Web Data Mining and Analysis #cs.IR
paper · pdf · doi:10.48550/arxiv.1807.02039
arxiv created 2018/07/05 · openalex publication_date 2018/07/05 · arxiv updated 2018/07/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Query Understanding is a semantic search method that can classify tokens in a customer's search query to entities such as Product, Brand, etc. This method can overcome the limitations of bag-of-words methods but requires an ontology. We show that current ontologies are not optimized for search and propose a simplified ontology framework designed specifically for e-commerce search and retrieval. We also present three methods for automatically extracting product classes for the proposed ontology and compare their performance relative to each other.