Indexeringen

Indexeringen, often called indexing, is the process of creating an index to support efficient retrieval, analysis, and sometimes calculation of data. The term is used across domains, with domain-specific implementations in information retrieval, databases, libraries, and economics.

In information retrieval and libraries, indexeringen often uses an inverted index, where each term points to the documents that contain it. The typical pipeline includes data collection, preprocessing (tokenization, normalization, stop-word removal, stemming), and index construction. The index is refreshed as new content is added and old content is modified or removed.

In databases, indexing refers to building data structures—such as B-trees or hash indexes—that speed up queries. Primary (clustered) indexes determine the physical order of data, while secondary (non-clustered) indexes support faster lookups. Index maintenance, including updates, insertions, and deletions, is a key consideration because indexes incur storage and write costs.

In economics and finance, indexeringen describes adjustments synchronized with a reference index. Common applications include inflation-linked contracts, pensions, wages, and prices that are periodically adjusted using indices such as the consumer price index (CPI).

Benefits of indexing include faster search and query performance and scalable data management. Drawbacks include storage overhead, maintenance complexity, and potential staleness if updates lag. Advances in distributed systems and machine learning improve index construction, relevance ranking, and update strategies, while privacy and data governance concerns shape how indexes are used.