indexedsearch

Indexed search, also known as full-text search, is a method of retrieving information from a collection of documents based on the content of the documents rather than just their metadata. This is achieved by first creating an index, which is a data structure that maps words or terms to the documents in which they appear. When a search query is performed, the index is consulted to quickly identify the relevant documents.

The process of creating an index typically involves several steps. First, documents are parsed to extract individual words or tokens. These tokens are then often normalized, meaning they are converted to a standard form, such as converting all words to lowercase or stemming them to their root form. Stop words, which are common words like "the" and "a" that are unlikely to be useful for searching, are usually removed. Finally, the remaining terms are stored in an inverted index, where each term is associated with a list of documents and their positions within those documents.

When a user submits a search query, the system breaks the query down into terms, normalizes them, and then looks them up in the inverted index. The index returns a list of documents containing those terms. Various algorithms and scoring mechanisms are then used to rank the retrieved documents by relevance to the query. This relevance is often determined by factors such as the frequency of the search terms in a document, their proximity to each other, and the overall importance of the terms within the document corpus. Indexed search is widely used in applications such as web search engines, database systems, and document management systems to provide efficient and effective information retrieval.