What is query expansion?
Query expansion is a technique used in information retrieval systems to improve search results by altering or expanding the original search query. It involves adding additional terms or phrases to the user's input to better match relevant documents and provide more accurate and comprehensive search results. This technique addresses the limitations of short or ambiguous user queries, helping search systems interpret user intent more effectively.
Types of query expansion
- Synonym Expansion: Adds synonyms of original query terms.
- Stemming and Lemmatization: Reduces words to their base or root form.
- Relevance Feedback: Uses user feedback on search results to refine queries.
- Automatic Thesaurus Generation: Employs a thesaurus to find and add related terms.
- Contextual Expansion: Expands queries based on the context of term usage
Application of query execution in an AI search engine
In AI search engines, query expansion enhances search functionality by:
- Improving search accuracy by including synonyms and related terms.
- Increasing recall by retrieving a larger set of relevant documents.
- Handling ambiguous queries by considering different meanings and contexts.
- Enhancing user experience by providing more comprehensive results.
- Leveraging AI and machine learning algorithms to improve expansion accuracy.
- Utilizing Natural Language Processing (NLP) for better understanding of user queries.
- Analyzing user behavior to tailor query expansion more effectively.