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JDOM

JDOM is an open-source Java-based document object model for XML that was designed specifically for the Java platform so that it can take advantage of its language features. JDOM integrates with Document Object Model (DOM) and Simple API for XML (SAX), supports XPath and XSLT. It uses external parsers to build documents. JDOM was developed by Jason Hunter…

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Products & Overview

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Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around JDOM. 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.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

License
Similar to Apache License
Operating system
Cross-platform
Repository
github.com/hunterhacker/jdom
Stable release
2.0.6.1 / December 9, 2021 (2021-12-09)
Type
XML binding
Written in
Java

Topics to explore

A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.

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

Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.

JDOM

Nodes11
Edges10
Triples12
Avg. degree1.82
Density0.181818
Components1

How this topic connects Entity context

Quick relationship hints grouped by predicate. Useful for spotting recurring semantic connections around the current entity.

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

JDOM

Top relations

related to Examples · 4
JDOM → Java, One, Suppose, XML
License · 1
JDOM → Similar to Apache License
Operating system · 1
JDOM → Cross-platform
Repository · 1
JDOM → github.com/hunterhacker/jdom
Stable release · 1
JDOM → 2.0.6.1 / December 9, 2021 (2021-12-09)
Type · 1
JDOM → XML binding
Website · 1
JDOM → jdom.org
Written in · 1
JDOM → Java
is a · 1
JDOM → open-source Java-based document object model for XML that was designed specifically for the Java platform so that it can take advantage of its language features

Important terminology Word statistics

Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.

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

Important terminology

xml java document object model external website open-source xpath xslt file one tree java-based designed specifically platform take advantage language

Entity relationships Subject–Predicate–Object triples

Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.
SubjectPredicateObjectConfidenceSrc
JDOMLicenseSimilar to Apache License1.00infobox
JDOMOperating systemCross-platform1.00infobox
JDOMRepositorygithub.com/hunterhacker/jdom1.00infobox
JDOMStable release2.0.6.1 / December 9, 2021 (2021-12-09)1.00infobox
JDOMTypeXML binding1.00infobox
JDOMWebsitejdom.org1.00infobox
JDOMWritten inJava1.00infobox
JDOMis aopen-source Java-based document object model for XML that was designed specifically for the Java platform so that it can take advantage of its language features0.90text
JDOMrelated to ExamplesSuppose0.60section
JDOMrelated to ExamplesXML0.60section
JDOMrelated to ExamplesOne0.60section
JDOMrelated to ExamplesJava0.60section

Related concept clusters Concept neighborhoods

Clusters of nearby vocabulary surrounding the topic. Scan them for adjacent concepts and language you may have missed.

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

    Connections between topic areas Semantic bridges

    Bridge nodes connect otherwise separate parts of the map. Expand a row to inspect the topic groups on each side.

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

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