{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T07:00:20Z","timestamp":1758265220313},"reference-count":8,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>\n            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 (\n            <jats:italic>SHOAL<\/jats:italic>\n            ) to bridge the gap between item taxonomy and user search intention. SHOAL organizes\n            <jats:italic>hundreds of millions of items<\/jats:italic>\n            into a\n            <jats:italic>hierarchical topic structure<\/jats:italic>\n            . 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.\n          <\/jats:p>","DOI":"10.14778\/3352063.3352084","type":"journal-article","created":{"date-parts":[[2019,9,18]],"date-time":"2019-09-18T18:36:11Z","timestamp":1568831771000},"page":"1858-1861","source":"Crossref","is-referenced-by-count":2,"title":["SHOAL"],"prefix":"10.14778","volume":"12","author":[{"given":"Zhao","family":"Li","sequence":"first","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xia","family":"Chen","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China and Southwest University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuming","family":"Pan","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengcheng","family":"Zou","sequence":"additional","affiliation":[{"name":"Alibaba Group, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuchen","family":"Li","sequence":"additional","affiliation":[{"name":"Singapore Management University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoxian","family":"Yu","sequence":"additional","affiliation":[{"name":"Southwest University, Chongqing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2019,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273576"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1103\/PhysRevE.69.026113"},{"key":"e_1_2_1_3_1","first-page":"403","volume-title":"EMNLP","author":"Tuan Luu A.","year":"2016","unstructured":"A. Tuan Luu , Y. Tay , S. C. Hui , and S. K. Ng . Learning term embeddings for taxonomic relation identification using dynamic weighting neural network . In EMNLP , pages 403 -- 413 , 2016 . A. Tuan Luu, Y. Tay, S. C. Hui, and S. K. Ng. Learning term embeddings for taxonomic relation identification using dynamic weighting neural network. In EMNLP, pages 403--413, 2016."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487631"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2005.09.007"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220064"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2556195.2556236"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031171.1031252"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3352063.3352084","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:40:47Z","timestamp":1672224047000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3352063.3352084"}},"subtitle":["large-scale hierarchical taxonomy via graph-based query coalition in e-commerce"],"short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":8,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["10.14778\/3352063.3352084"],"URL":"https:\/\/doi.org\/10.14778\/3352063.3352084","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2019,8]]}}}