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Millions of people use online e-commerce platforms to search and buyproducts. Identifying attributes in a query is a critical component inconnecting users to relevant items. However, in many cases, the queries havemultiple attributes, and some of them will be in conflict with each other. Forexample, the query "maroon 5 dvds" has two candidate attributes, the color"maroon" or the band "maroon 5", where only one of the attributes can bepresent. In this paper, we address the problem of resolving conflictingattributes in e-commerce queries. A challenge in this problem is that knowledgebases like Wikipedia that are used to understand web queries are not focused onthe e-commerce domain. E-commerce search engines, however, have access to thecatalog which contains detailed information about the items and its attributes.We propose a framework that constructs knowledge graphs from catalog to resolveconflicting attributes in e-commerce queries. Our experiments on real-worldqueries on e-commerce platforms demonstrate that resolving conflictingattributes by leveraging catalog information significantly improves attributeidentification, and also gives out more relevant search results.

Leveraging Catalog Knowledge Graphs for Query Attribute Identification in E-Commerce Sites