SHOAL
| Autor: | Xia Chen, Guoxian Yu, Xuming Pan, Pengcheng Zou, Zhao Li, Yuchen Li |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
geography
Information retrieval geography.geographical_feature_category Topic structure business.industry Computer science Graph based General Engineering Shoal 02 engineering and technology E-commerce Click-through rate 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing business |
| Zdroj: | Proceedings of the VLDB Endowment. 12:1858-1861 |
| ISSN: | 2150-8097 |
| Popis: | E-commerce taxonomy plays an essential role in online retail business. Existing taxonomy of e-commerce platforms organizes items into an ontology structure. However, the ontology-driven approach is subject to costly manual maintenance and often does not capture user's search intention, particularly when user searches by her personalized needs rather than a universal definition of the items. Observing that search queries can effectively express user's intention, we present a novel large-Scale Hierarchical taxOnomy via grAph based query coaLition ( SHOAL ) to bridge the gap between item taxonomy and user search intention. SHOAL organizes hundreds of millions of items into a hierarchical topic structure . Each topic that consists of a cluster of items denotes a conceptual shopping scenario, and is tagged with easy-to-interpret descriptions extracted from search queries. Furthermore, SHOAL establishes correlation between categories of ontology-driven taxonomy, and offers opportunities for explainable recommendation. The feedback from domain experts shows that SHOAL achieves a precision of 98% in terms of placing items into the right topics, and the result of an online A/B test demonstrates that SHOAL boosts the Click Through Rate (CTR) by 5%. SHOAL has been deployed in Alibaba and supports millions of searches for online shopping per day. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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