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KMPlayer: History, Subtitles & Overview
K-Multimedia Player (commonly known as The KMPlayer, KMPlayer or KMP) is an Adware-supported media player for Windows, android and iOS that can play most current audio and video formats, including VCD, DVD, AVI, MP4, MPG, DAT, OGM, VOB, MKV, Ogg, OGM, 3GP, MPEG-1/2/4, AAC, WMA 7/8, WMV, RealMedia, FLV, and QuickTime.
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KMPlayer topic overview
The analysis highlights History, Subtitles and Overview as prominent areas in the source structure around KMPlayer.
Related topics
40
Source areas
4
Connected nodes
44
Extracted relationships
32
Concept neighborhoods
23
Bridge connections
44
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Overview · 19 topics
Subtitles · 15 topics
Reception · 4 topics
History · 2 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Windows 10 and later · OS X 10.6 or later · Android 7.0 or later · iOS 13 or later
Original author
Kang Yong-Huee
Release
1 October 2002; 23 years ago (2002-10-01)
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How KMPlayer connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around KMPlayer shows recurring relationship patterns in the source. For example, KMPlayer → August, Kang Yong-Huee, Korean, March, October, On, Pandora TV, The KMPlayer's Forum Another extracted example is KMPlayer → In, KMP, Player, The, The About, The KMPlayer, The KMPlayer Professional Media. Use these groups to spot repeated connection types before inspecting the individual relationships.
KMPlayer
Top relations
related to history· 8
KMPlayer → August, Kang Yong-Huee, Korean, March, October, On, Pandora TV, The KMPlayer's Forum
related to Naming· 7
KMPlayer → In, KMP, Player, The, The About, The KMPlayer, The KMPlayer Professional Media
related to Reception· 5
KMPlayer → CNET's Download, If, In, Lifehacker, Seth Rosenblatt
Operating system· 4
KMPlayer → Android 7.0 or later, iOS 13 or later, OS X 10.6 or later, Windows 10 and later
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 32 structured relationships around KMPlayer. Examples in this analysis include KMPlayer → Available in → English, Afrikaans, Amharic, Arabic, Bulgarian, Catalan, Croatian, Czech, Danish, Dutch, Estonian, Finnish, French, German, Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian,… and KMPlayer → Developer → Pandora TV. The table shows each extracted connection, where it came from and its confidence.
Delphi, C++Builder, Netwide Assembler and Visual C++
1.00
infobox
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around KMPlayer bring nearby vocabulary together. In this analysis, examples include Player, Kmp and Media. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
KMPlayer
Player
Kmp
Media
Video
Also
Page
Referred
Windows
Available
Com
Freeware
Korean
kmplayer
Player
Kmp
Media
Video
Also
Page
Referred
Windows
Available
Com
Freeware
Korean
android
Ios
Windows
Avi
Dvd
Flv
Kang
Media
Ogg
Quicktime
Realmedia
Vcd
Wmv
ios
Windows
Avi
Dvd
Flv
Kang
Media
Ogg
Quicktime
Realmedia
Vcd
Wmv
Yong-huee
3gp
Mkv
Mp4
Ogm
Vob
Avi
Dvd
Flv
Ogg
Quicktime
Realmedia
Vcd
Wmv
wmv
Avi
Dvd
Flv
Ogg
Quicktime
Realmedia
Vcd
3gp
Android
Formats
Ios
K-multimedia
formats
Windows
Avi
Dvd
Flv
Media
Ogg
Quicktime
Realmedia
Vcd
Wmv
Video
3gp
dvd
Avi
Flv
Ogg
Quicktime
Realmedia
Vcd
Wmv
3gp
Formats
Ios
K-multimedia
Mkv
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For KMPlayer, one of the stronger structural bridges in this analysis connects KMPlayer with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
KMPlayer
Nodes45
Edges44
Triples32
Avg. degree1.96
Density0.044444
Components1
Source & methodology
TTTA analyzes the structure around KMPlayer to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Subtitles & Overview, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
