The task is to assign a web search query to one or more predefined categories, based on its topics.
Online advertisement services can rely on the query classification results to promote different products more accurately.
Search result pages can be grouped according to the categories predicted by a query classification algorithm.
For example, "apple" could refer to a type of fruit or a computer company, while "Java" could signify a programming language or an island in Indonesia.
Query-enrichment based methods[1][2] start by enriching user queries to a collection of text documents through search engines.
Thus, each query is represented by a pseudo-document which consists of the snippets of top ranked result pages retrieved by search engine.
This classifier is then used in an online mode to map user queries to the target categories via the intermediate taxonomy.
The advantage of this approach is that the bridging classifier needs to be trained only once and is adaptive for each new set of target categories and incoming queries.