Describe the process of query expansion in information retrieval.

Query expansion is a technique used in information retrieval to improve the effectiveness of search queries by adding additional terms or concepts to the original query. The process of query expansion involves the following steps:

1. Initial query formulation: The user enters a query consisting of one or more keywords or phrases to retrieve relevant information from a search engine or database.

2. Term selection: The system analyzes the initial query and identifies the most important terms or concepts. These terms are typically referred to as the query's "core terms."

3. Expansion terms identification: The system then identifies additional terms or concepts related to the core terms. This can be done using various methods such as synonym identification, word sense disambiguation, or statistical analysis of co-occurring terms in a large corpus of documents.

4. Expansion term selection: From the identified expansion terms, the system selects the most relevant ones to add to the original query. The selection can be based on factors such as term frequency, term relevance, or user preferences.

5. Query modification: The selected expansion terms are added to the original query, either by appending them to the end or inserting them at appropriate positions. The modified query is then sent to the search engine or database for retrieval.

6. Result retrieval and ranking: The search engine or database retrieves documents that match the modified query and ranks them based on their relevance to the expanded query. The ranked results are then presented to the user.

7. Evaluation and feedback: The user evaluates the retrieved results and provides feedback to the system. This feedback can be used to refine the query expansion process in subsequent searches, improving the overall retrieval effectiveness.

Overall, query expansion aims to enhance the retrieval process by broadening the scope of the original query and capturing a wider range of relevant documents. It helps overcome limitations such as term mismatch, synonymy, or polysemy, and improves the precision and recall of information retrieval systems.