Techniques for Deep Query Understanding
This is an incremental review of techniques for improving search engine relevance, primarily benefiting developers and researchers in information retrieval.
The report tackles the challenge of inferring precise user intent from short and ambiguous search queries by describing a complete architecture for query understanding, including correcting user mistakes, guiding query formulation, and inferring intent, but does not provide concrete numerical results.
Query Understanding concerns about inferring the precise intent of search by the user with his formulated query, which is challenging because the queries are often very short and ambiguous. The report discusses the various kind of queries that can be put to a Search Engine and illustrates the Role of Query Understanding for return of relevant results. With different advances in techniques for deep understanding of queries as well as documents, the Search Technology has witnessed three major era. A lot of interesting real world examples have been used to illustrate the role of Query Understanding in each of them. The Query Understanding Module is responsible to correct the mistakes done by user in the query, to guide him in formulation of query with precise intent, and to precisely infer the intent of the user query. The report describes the complete architecture to handle aforementioned three tasks, and then discusses basic as well as recent advanced techniques for each of the component, through appropriate papers from reputed conferences and journals.