Contextual retrieval is an IR technique that aims to consider the context in which a query is made to improve search relevance. Unlike traditional retrieval methods that rely primarily on keyword matching, contextual retrieval takes into account factors like the user’s intent, prior interactions, or the surrounding content of the query.
For example, a contextual retrieval system may use machine learning models or natural language processing (NLP) techniques to understand the context of a search query, such as distinguishing between a “bank” referring to a financial institution or the side of a river. This helps the system retrieve more precise and relevant results.
Contextual retrieval is increasingly important with the rise of conversational agents, voice search, and personalized search experiences, where understanding the user’s context is crucial for providing meaningful results.