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In computer science, an inverted index (also referred to as a postings list, postings file, or inverted file) is a database index storing a mapping from content, such as words or numbers, to its locations in a table, or in a document or a set of documents (named in contrast to a forward index, which maps from documents to content). [1]
A KWIC index is a special case of a permuted index. [4] This term refers to the fact that it indexes all cyclic permutations of the headings. Books composed of many short sections with their own descriptive headings, most notably collections of manual pages, often ended with a permuted index section, allowing the reader to easily find a section by any word from its heading.
The specificity describes how closely the index terms match the topics they represent [10] An index is said to be specific if the indexer uses parallel descriptors to the concept of the document and reflects the concepts precisely. [11] Specificity tends to increase with exhaustivity as the more terms you include, the narrower those terms will be.
A document retrieval system consists of a database of documents, a classification algorithm to build a full text index, and a user interface to access the database. A document retrieval system has two main tasks: Find relevant documents to user queries; Evaluate the matching results and sort them according to relevance, using algorithms such as ...
Microsoft Access has two built-in utilities, Database Splitter [53] and Linked Table Manager, to facilitate this architecture. Linked tables in Access use absolute paths rather than relative paths, so the development environment either has to have the same path as the production environment or a "dynamic-linker" routine can be written in VBA.
Index terms can consist of a word, phrase, or alphanumerical term. They are created by analyzing the document either manually with subject indexing or automatically with automatic indexing or more sophisticated methods of keyword extraction. Index terms can either come from a controlled vocabulary or be freely assigned.
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The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects.