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VP-Info: Technical, Marketing & Origin
VP-Info is a database language and compiler for the personal computer. VP-Info was a competitor to the Clipper and dBase applications in the late 1980s and 1990s. VP-Info was originally intended to run on MS-DOS, DR-DOS and the PC-MOS/386 operating system, but now is run on the vDOS, or DOSbox-X, emulators. The last release of VP-Info, a multi-tasking…
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VP-Info topic overview
The analysis highlights Technical, Marketing and Origin as prominent areas in the source structure around VP-Info.
Related topics
24
Source areas
6
Connected nodes
30
Extracted relationships
71
Concept neighborhoods
13
Bridge connections
30
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 · 9 topics
Technical · 6 topics
Marketing · 4 topics
Origin · 3 topics
Reception · 1 topics
Versions · 1 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.
Developer
Paperback Software International Ltd.
Release
1986
Type
database language & compiler
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 VP-Info 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 VP-Info shows recurring relationship patterns in the source. For example, VP-Info → Clark, Clark's, ComputerLand, David, David Clark, For, George Gratzer, Gratzer, Gratzer's, II, III, In, Manitoba, Max, Paperback Software, Standard Knitting, Sub Rosa, The, This, University Another extracted example is VP-Info → Bernie Melman, Bursten, Lotus, Lotus Development Corp, Max, Minneapolis, Paperback Software, Paperback Software International Ltd, Shark, SharkBase, Since, Specialized Clinical Services, Sub Rosa Corporation, Sub Rosa Inc, Sub Rosa Publishing Inc, Though, Toronto, VP-Planner. Use these groups to spot repeated connection types before inspecting the individual relationships.
VP-Info
Top relations
related to Origin· 23
VP-Info → Clark, Clark's, ComputerLand, David, David Clark, For, George Gratzer, Gratzer, Gratzer's, II, III, In, Manitoba, Max, Paperback Software, Standard Knitting, Sub Rosa, The, This, University
related to Marketing· 18
VP-Info → Bernie Melman, Bursten, Lotus, Lotus Development Corp, Max, Minneapolis, Paperback Software, Paperback Software International Ltd, Shark, SharkBase, Since, Specialized Clinical Services, Sub Rosa Corporation, Sub Rosa Inc, Sub Rosa Publishing Inc, Though, Toronto, VP-Planner
related to Versions· 12
VP-Info → All, LAN, Multi-user/multi-tasking, NetBios, SharkBase, SharkBase Network Edition, SR-Info, The Network Editions, VP-Info Level, VP-Info Professional, VP-Info Professional Network Edition, Windows
related to Technical· 11
VP-Info → Clipper, However, II, III, IV, On, OpenOffice, PCs, SSDs, Unlike, VP-Info/Shark
related to Reception· 2
VP-Info → InfoWorld, More
Developer· 1
VP-Info → Paperback Software International Ltd.
Release· 1
VP-Info → 1986
Type· 1
VP-Info → database language & compiler
is a· 1
VP-Info → database language and compiler for the personal computer
Important terminology
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.
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 71 structured relationships around VP-Info. Examples in this analysis include VP-Info → Developer → Paperback Software International Ltd. and VP-Info → Release → 1986. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
VP-Info
Developer
Paperback Software International Ltd.
1.00
infobox
VP-Info
Release
1986
1.00
infobox
VP-Info
Type
database language & compiler
1.00
infobox
VP-Info
is a
database language and compiler for the personal computer
0.90
text
PC-MOS/386
instance of
and also on multi-user/multi-tasking systems with NetBIOS over TCP/IP
0.80
text
VP-Info
related to Marketing
Paperback Software International Ltd
0.60
section
VP-Info
related to Marketing
Max
0.60
section
VP-Info
related to Marketing
Lotus Development Corp
0.60
section
VP-Info
related to Marketing
VP-Planner
0.60
section
VP-Info
related to Marketing
Lotus
0.60
section
VP-Info
related to Marketing
Paperback Software
0.60
section
VP-Info
related to Marketing
Though
0.60
section
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 VP-Info bring nearby vocabulary together. In this analysis, examples include Files, Dbf and Distribution. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
dbase
Ii
Clark
Language
Time
Files
Vp-info
Dbf
Gratzer
Release
Emulator
Max
Rosa
dbase ii
Time
Ii
Clark
Language
Files
Vp-info
Dbf
Gratzer
Max
Rosa
Speed
Sub
compiler
Release
Built-in
Database
Language
Shark
Vp-info
Sharkbase
Emulator
Gratzer
Multi-tasking
Speed
Version
database language
Language
Gratzer
Clark
Compiler
Dbase
Release
Emulator
Max
Rosa
Speed
Sub
Ii
emulator
Windows
Using
Vdos
Versions
Run
Ms-dos
Release
Sharkbase
Gratzer
Multi-tasking
Clark
Language
paperback software international ltd.
Ltd
Software
International
Paperback
Published
Worldwide
Max
Versions
Vp-info
Back
Version
Program
VP-Info
Files
Dbf
Distribution
Windows
Back
Rosa
Sub
Using
Worldwide
Time
Max
Published
vp-info
Files
Dbf
Distribution
Windows
Back
Rosa
Sub
Using
Worldwide
Time
Max
Published
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 VP-Info, one of the stronger structural bridges in this analysis connects VP-Info 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.
VP-Info
Nodes31
Edges30
Triples71
Avg. degree1.94
Density0.064516
Components1
Source & methodology
TTTA analyzes the structure around VP-Info to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Technical, Marketing & Origin, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
