Research this topic
Explore the main themes, entities and connections around Cron. 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.
History
Overview
Cron expression
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
- Developer
- AT&T Bell Laboratories
- Operating system
- Unix and Unix-like, Plan 9, Inferno
- Release
- May 1975; 51 years ago (1975-05)
- Type
- Job scheduler
- Written in
- C
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
- Job scheduler
- At At (command)
- Chronos
- Unix-like
- Operating systems Operating system
- Daemon Daemon (computer software)
- Bourne shell
- 4th BSD edition Berkeley Software Distribution
- Paul Vixie
- Nncron NnCron?action=edit&redlink=1
- Debian
- Init
- DST
History
- Version 7 Unix
- Daemon Daemon (computing)
- Algorithm
- Superuser
- Purdue University
- VAX
- Unix System V
- MIPS Instructions per second
- Communications of the ACM
- Complexity Analysis of algorithms
- Discrete event simulators Discrete event simulation
- SIGHUP
- Unix System V
- Solaris Solaris (operating system)
- Sun Microsystems
- IRIX
- Silicon Graphics
- HP-UX
- Hewlett-Packard
- AIX IBM AIX
- IBM
- GNU Project
- Linux
- ISC Internet Systems Consortium
- Red Hat
- Cronie
- Anacron
- DragonFly DragonFly BSD
- Matt Dillon Matthew Dillon (computer scientist)
- Guile GNU Guile
Cron expression
- Hyphen Hyphen-minus
- Quartz Java scheduler Quartz (scheduler)
- Jenkins Jenkins (software)
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.Cron
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.
Cron
Top relations
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
time crontab daemon system job user run version file must users used task unix also scheduling files command event list
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Cron | Developer | AT&T Bell Laboratories | 1.00 | infobox |
| Cron | Operating system | Unix and Unix-like, Plan 9, Inferno | 1.00 | infobox |
| Cron | Release | May 1975; 51 years ago (1975-05) | 1.00 | infobox |
| Cron | Type | Job scheduler | 1.00 | infobox |
| Cron | Written in | C | 1.00 | infobox |
| Cron | is a | time-based job scheduler | 0.90 | text |
| Cron | is a | mere pattern-matcher | 0.90 | text |
| first-weekday | instance of | as well as supporting additional expression features | 0.80 | text |
| last-day-of-month.Nonstandard predefined scheduling definitionsSome cron implementations support the following non-standard macros | instance of | as well as supporting additional expression features | 0.80 | text |
| PAM | instance of | adding features | 0.80 | text |
| SELinux support | instance of | adding features | 0.80 | text |
| predefined schedules | instance of | with future versions planned to incrementally add features | 0.80 | text |
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.