SHOAL: Large-scale hierarchical taxonomy via graph-based query coalition in E-commerce

• Main Authors: LI, Zhao, CHEN, Xia, PAN, Xuming, ZOU, Pengcheng, LI, Yuchen, YU, Guoxian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Computer Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4620; https://ink.library.smu.edu.sg/context/sis_research/article/5623/viewcontent/p1858_li.pdf
• Institution: Singapore Management University

E-commerce taxonomy plays an essential role in online retail business. Existing taxonomy of e-commerce platformsorganizes items into an ontology structure. However, theontology-driven approach is subject to costly manual maintenance and often does not capture user’s search intention,particularly when user searches by her personalized needsrather than a universal definition of the items. Observingthat search queries can effectively express user’s intention,we present a novel large-Scale Hierarchical taxOnomy viagrAph based query coaLition (SHOAL) to bridge the gapbetween item taxonomy and user search intention. SHOALorganizes hundreds of millions of items into a hierarchicaltopic structure. Each topic that consists of a cluster of itemsdenotes a conceptual shopping scenario, and is tagged witheasy-to-interpret descriptions extracted from search queries.Furthermore, SHOAL establishes correlation between categories of ontology-driven taxonomy, and offers opportunitiesfor explainable recommendation. The feedback from domainexperts shows that SHOAL achieves a precision of 98% interms of placing items into the right topics, and the resultof an online A/B test demonstrates that SHOAL boosts theClick Through Rate (CTR) by 5%. SHOAL has been deployed in Alibaba and supports millions of searches for online shopping per day.