Abstract
Search engines aim at helping users find relevant results from the Web. Understanding the underlying intent of queries issued to search engines is a critical step toward this goal. Till now, it is still a challenge to have a scientific definition of query intent. Existing approaches attempting to understand query intents can be classified into two categories: (1) query intent classification: mapping queries into categories and (2) query intent mining: finding subtopics covered by the queries. For the first group of work, the mapping between queries and categories can be conducted in various ways, including classifying based on navigational, informational, or transactional intent, based on geographic locality, temporal intent, topical categories, or available vertical services. For query intent mining, the output can be a list of explicit subqueries, or some implicit representation of subintent, such as a list of document clusters, a list of entities, etc. In this chapter, we will introduce these query intent prediction approaches in detail.
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Dou, Z., Guo, J. (2020). Query Intent Understanding. In: Chang, Y., Deng, H. (eds) Query Understanding for Search Engines. The Information Retrieval Series, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-030-58334-7_4
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