Indexing in information retrieval is the process of collecting, parsing, and storing data to enable fast and accurate retrieval of relevant information. It involves creating structured indexes from a collection of documents or data so that search systems can quickly locate relevant items without scanning every document individually. The index acts as a lookup structure mapping terms or keywords to the documents where they appear. In essence, indexing optimizes search speed and performance by organizing data to support efficient query processing. Without indexing, a search engine or retrieval system would have to sequentially scan all documents for query terms, which is time-consuming and computationally expensive. Key aspects of indexing include:

• Providing access points to information through identifiers such as keywords.
• Using data structures like inverted indexes that map terms to document occurrences.
• Applying processes such as tokenization, stop-word removal, and stemming during index creation.
• Maintaining and updating the index to reflect changes in the data.

This process is fundamental in various information retrieval systems, including search engines, digital libraries, and databases, facilitating quick and relevant search results. Thus, indexing in information retrieval can be summarized as the creation of an organized data structure that allows efficient and scalable searching by associating terms with their corresponding documents or records.