Indexing software
The topic of Indexing software is widely known and discussed today. Since people began to talk about Indexing software, it has generated great interest and has been the subject of numerous studies and research. In this article we will analyze different aspects related to Indexing software, from its origin and evolution to its impact on current society. In addition, we will explore the different opinions and perspectives that exist around Indexing software, with the aim of providing a complete and enriching vision of this very relevant topic.
Indexing software consists of computer applications that help to build an index.[1]
Features
There are several methodologies for indexing:[1][2]
- Standalone indexing applications enable an indexer to create an index as a separate document, later to be integrated into the original text, by manually entering headings and page numbers or other locators. Such applications collate, alphabetize, and sort the raw input to create a formatted index.
- Embedded indexing includes the index headings in the midst of the text itself, but surrounded by codes so that they are not normally displayed. A usable index is then generated automatically from the embedded text using the position of the embedded headings to determine the locators. Thus, when the pagination is changed the index can be regenerated with the new locators.
- Tagging allows indexing codes to be embedded in the text after the indexing is complete. The indexer inserts numbered dummy tags in the files, and then builds the index separately
- Many word processors and desktop publishing software have integrated automated indexing functions. These tools build a concordance or word lists from processed files. They have often limited usage.
- AI and machine-learning approaches have not yet matured to the point where they can create finished or near-finished indexes.
See also
References
- ^ a b "Software". asindexing.org. The American Society for Indexing. Retrieved 2017-01-07.
- ^ Golub, Koraljka (2019). "Automatic subject indexing of text (IEKO)". Knowledge Organization. 46 (2): 104–121. doi:10.5771/0943-7444-2019-2-104. S2CID 108348599. Retrieved 2022-06-03.
 | This computing article is a stub. You can help Wikipedia by expanding it. |