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Full-text database

A full-text database (or complete-text database) is a database that contains the full text of books, dissertations, journals, magazines, newspapers or other textual documents. It differs from bibliographic databases, which typically contain only bibliographic metadata and sometimes abstracts, and from other non-bibliographic databases such as directories…

Overview, Related Topics & Entities

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Research this topic

Explore the main themes, entities and connections around Full-text database. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Full-text database

Nodes19
Edges18
Triples10
Avg. degree1.89
Density0.105263
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

full-text database retrieval text databases bibliographic typically systems information full 1990 search books dissertations journals magazines newspapers documents metadata abstracts

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
directoriesinstance ofand from other non-bibliographic databases0.80text
numeric databases.One of the earliest systems of this type was IBM STAIRSinstance ofand from other non-bibliographic databases0.80text
introduced in 1973.Full-text databases became more widespread around 1990instance ofand from other non-bibliographic databases0.80text
when advances in computer storageinstance ofand from other non-bibliographic databases0.80text
processing made large-scale text storageinstance ofand from other non-bibliographic databases0.80text
retrieval more practicalinstance ofand from other non-bibliographic databases0.80text
BRSinstance ofon hosts0.80text
Dialoginstance ofon hosts0.80text
LexisNexisinstance ofon hosts0.80text
and Westlawinstance ofon hosts0.80text

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.