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LinuxDoc

LinuxDoc is an SGML DTD which is similar to DocBook. Matt Welsh created it, and version 1.1 was announced in 1994. It is primarily used by the Linux Documentation Project. The DocBook SGML tags are often longer than the equivalent LinuxDoc tags.

Overview, Related Topics & Entities

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Research this topic

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

Explore this topic

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Topics to explore

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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

LinuxDoc

Nodes10
Edges9
Triples7
Avg. degree1.8
Density0.2
Components1

How this topic connects Entity context

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

LinuxDoc

Top relations

related to External links · 6
LinuxDoc → Howtos-with-LinuxDoc, HTML, JavaScript, Linux/docs/HOWTO/other-formats/, LinuxDocSample, SGMLTools
is a · 1
LinuxDoc → SGML DTD which is similar to DocBook

Important terminology Word statistics

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

Important terminology

docbook linux sgml dtd debian similar matt welsh created version announced 1994 primarily used documentation project tags often longer equivalent

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
LinuxDocis aSGML DTD which is similar to DocBook0.90text
LinuxDocrelated to External linksLinux/docs/HOWTO/other-formats/0.60section
LinuxDocrelated to External linksHowtos-with-LinuxDoc0.60section
LinuxDocrelated to External linksJavaScript0.60section
LinuxDocrelated to External linksLinuxDocSample0.60section
LinuxDocrelated to External linksHTML0.60section
LinuxDocrelated to External linksSGMLTools0.60section

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
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