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Knowledge graphs are recently used for enriching query representations in an entity-aware way for the rich facts organized around entities in it. However, few of the methods pay attention to non-entity words and clicked websites in queries, which also help conveying user intent. In this paper, we tackle the problem of intent understanding with innovatively representing entity words, refiners and clicked urls as intent topics in a unified knowledge graph based framework, in a way to exploit and expand knowledge graph which we call ‘tailor’. We collaboratively exploit global knowledge in knowledge graphs and local contexts in query log to initialize intent representation, then propagate the enriched features in a graph consisting of intent topics using an unsupervised algorithm. The experiments prove intent topics with knowledge graph enriched features significantly enhance intent understanding.

Tailor knowledge graph for query understanding: linking intent topics by propagation