LlamaIndex handles query expansion by enhancing user queries to improve the relevance of search results within its information retrieval framework. Query expansion is a technique used to augment a user’s original query with additional terms or synonyms, making it more comprehensive and likely to yield better results. In LlamaIndex, this process usually involves analyzing the context of the terms within the query and then identifying related concepts or keywords that can be added to broaden the scope of the search.
For instance, when a user inputs a query like "best programming languages," LlamaIndex may expand this query by including variations such as "top programming languages," or even specific languages like "Python," "Java," or "C#." This is achieved through an understanding of the terminology and the typical associations it has with other words in the database. By doing so, LlamaIndex can ensure that the results returned are not only more varied but also more closely aligned with what the user might be looking for.
Additionally, LlamaIndex uses techniques like relevance feedback and user interaction history to refine the expansion over time. If users frequently click on certain types of results or specific content related to a specific expanded term, LlamaIndex can learn from these patterns and adjust its query expansion strategy accordingly. This adaptive approach means that, as LlamaIndex interacts more with users, it becomes better at anticipating their needs, thus continuously improving the quality of search results derived from expanded queries.