Study Muddy
Study Muddy

Upload, organize, preview, and share study documents from one clean workspace.

Explore

BrowseAbout UsContact Us

Workspace

UploadDashboard

Legal

Privacy PolicyTerms & ConditionsDisclaimerReport Copyright & Abuse
Study Muddy
PDF·0% (0)·0 views·9 pages

Diagrammatic Description Logic: Graphs and Conceptual Graphs

An article on diagrammatic description logic covering graphs, multigraphs, semantic nets, graph homomorphism, conceptual graphs, and hyper-graphs.

Category: Travel

Uploaded by Jordan Mitchell on Apr 23, 2026

Copyright

© All Rights Reserved

We take content rights seriously. If you suspect this is your content, claim it here.

Available Formats

Download as PDF or TXT.

Download PDF
/ 9
100%
9

Document text

Diagrammatic Description Logic

Definition 1 (Graph).

A graph(V,E) consists of a set V of vertices and a set E of edges.

Every edge in E is a pair of vertices from the set V.

Note that our graphs are always directed.

It means that each E element is a pair (vs,vd) where vs is the source vertex of the

edge and vd is the destination vertex of the edge.

Labels. An essential graph equipment is labels. Unlabeled graph are useless

abstract graphs. Concrete graph are always labeled. Either only the vertices are

labeled, or both vertices and edges are labeled. Edge labels (is they exist) support

an information about the connection from the source vertex to the destination

vertex.

Example. An utterly abstract graph. Yet, just label each vertex by a character

and it becomes a lexical automaton that parses only the English words race, rat,

ray, rice, ride, role, rome, rope, rose, row, rude, rule.

Fig. 1 The abstract graph Fig. 2 The same vertex-labeled graph

Definition 2 (Multigraph).

Because they are eventually multiple pertinent connections from the source

vertex to the destination vertex, sometimes multiple edges from the same source

to the same destination are needed, each supporting one label.

A multigraph(V,E) is a graph(V,E) where E is a multiset.

Example.

Sarah is the spouse and colleage of John.

Fig. 3 Finally edges are labeled too

1

Another example.

Estimated cost but largeur exact revenue.

Fig. 4 Great benefits

Definition 3 (Cycle).

A graph path that starts and ends with the exact same vertex is a cycle.

Example.

John and Sarah are husband and wife.

Fig. 5 We go full circle

Definition 4 (DAG).

A graph without a cycle is a directed acyclic graph or DAG.

Definition 5 (Semantic Net).

A semantic net is a multigraph whose vertices are labeled with concepts and

whose edges are labeled with inter-concept relations.

A prominent inter-concept relation is the isA relation.

The isA relation asserts that the source concept is a subtype of the destination

concept. As a subtype relation the isA relation is transitive and forms a DAG.

Semantic net is the first historically acclaimed, and widely used, graph formalism

that allows some powerful knowledge representation (KR). Starting with KL-

One, a KR language family finally distinguished itself from the venerable Lisp

and Prolog. The isA subtype relation leads to the notion of graph-

homomorphism which is today recognized as a privileged tool to request and

manipulate KR databases.

2

Example.

Socrates life and intellectual legacy.

Fig. 6 Socrates

Definition 6 (Graph homomorphism).

A graph homomorphism H is a mapping from a graph G(V,E) to a graph G'(V',E')

so that :

informally : every image (by H) of an edge of G is an edge of G'

formally : if (vs,vd) ∈ E then H(vs,vd) = (vs',vd') ∈ E'

Example.

As graph homomorphism is an abstract thing it deserves an abstract example.

Fig. 7 H is a mapping from the abstract graph G to the abstract graph G’

3

Definition 7 (Graph subsumption).

A graph G subsumes a graph G' if there exists a graph homomorphism H from G

to G’ and H matches the isA inverse relation.

Example.

A cat is on a mat.

Fig. 8 H is a homomorphism from bottom to top

It is quite straithforward that :

A cat is a kind of animal.

To be on something is a kind of relation.

A mat is a kind of artifact.

H is a graph homomorphism from bottom to top.

Hence the bottom graph subsumes the top graph.

Definition 8 (Bipartite graph).

A bipartite graph is a graph whose vertices can be divided into two disjoint sets

V1 and V2 (that is, V1 and V2 are each independent sets) such that any edge

connects a vertex in V1 to one in V2 or a vertex in V2 to one in V1.

Graphically.

It is common practice to draw one kind of vertices as square boxes and the other

kind of vertices as rounded boxes. Hence, in a bipartite graph drawing, a square

box can only connect to rounded boxes, and a rounded box can only connect to

square boxes.

Fig. 9 An abstract bipartite graph

4

Definition 9 (Conceptual graph).

A conceptual graph (CG) is a bipartite multigraph whose square vertices are

labeled with entities and whose rounded vertices are labeled with inter-entity

relations.

Apart that, a conceptual graph features an implicit isA relation and works much

like a semantic net, especially regarding graph subsumption capabilities. The

isA relations used by a conceptual graph are made explicit by the graph

database ontology. The graph vocabulary is also stored by the ontology.

Example.

A rich man gives some cash to a beggar.

Fig. 10 A simple conceptual graph

The facts that the edge n°1 is the giver, the edge n°2 is the gift and the edge n°3

is the beneficiary are recorded in the graph database ontology.

Definition 10 (Nested conceptual graph).

A nested conceptual graph is a conceptual graph whose square vertices can

contain further nested conceptual graph. Eventually, some generalized nested

conceptual graph formalism can allow edges to traverse square box boundaries in

any manner (from inside to outside, from outside to inside, whatever the nesting

level). Nested graphs provide a direct visual way to decorate the information with

the associated context.

Discussion.

Semantic nets are now a somewhat deprecated way of KR. On the practical side

they have been superceded by the RDF-OWL web standard. On the theoritical

side they have been superceded by (nested) conceptual graphs that provide a

better basis for everything from formal semantic to formal reasoning assistance.

Example.

Eva dreams about a clown show. A sponsor makes her an offer of a man to act as

the clown and the funds to finance the event.

5

Fig. 11 A generalized nested conceptual graph

Discussion.

Some people argue that generalized nested conceptual graphs are no more graphs

but free full diagrams. Anyway, even if so, then generalized nested conceptual

graph is the first attempt to formalize free full diagrams.

Definition 11 (Coreference link).

A coreference link is an equality relation connecting 2 entities across 2 contexts.

Graphically. The coreference link is usually drawn as a dotted line connecting

two square boxes. Coreference links are transitive.

Motivation. In a nested conceptual graph, a same entity box can appear in

multiple contexts. Would this equality not be explicited by coreference link(s),

the reader could misbelieve that each separate box is a fresh new entity.

Example.

A woman looks a photograph with her at Venise.

Fig. 12 A nested conceptual graph with one coreference link

6

Discussion.

One can argue that there is actually no woman on a photograph, but merely a

woman portrait. Thus the woman and the woman picture are not really the same

entity as suggested by the coreference link. For example the woman portrait has

red eyes and it’s not a woman property, it’s a portrait property. However a

coreference link is only equality modulo context, and the pictured woman is the

same as the looker woman.

Another example.

The man that wants to kill his dog tells he has rabies.

Fig. 13 A nested conceptual graph with 3 coreference links

Definition 12 (Difference link).

A difference link is a relation that denies the equality between two entities.

Graphically. The difference link between two square boxes is usually drawn as

a line with a double stroke reminding the ≠ symbol.

Motivation. Difference links are most useful to avoid unwanted subsumption.

Example.

Fig. 14 Without the difference link, the left CG would subsume the right CG

7

Definition 13 (Negated relation).

A negated relation can be used to deny some relation with one (or more) entity.

Graphically. A relation with square boxe(s) can be negated by the ¬ symbol.

Motivation. Negated relations are most useful to avoid unwanted subsumption.

Example.

Fig. 15 How a sponsor selects a champion recruit

Definition 14 (Hyper-graph).

An hyper-graph(V,E) is a graph(V,E) whose edges are tuples (v1,v2,...,vn) rather

than merely pairs. Thus an hyper-edge can connect many vertices. A monadic

edge is an edge that decorates 1 vertex. A dyadic edge is an edge that connects 2

vertices. A triadic edge connects 3 vertices.

Example.

Fig. 16 An abstract hyper-graph Fig. 17 A labeled hyper-graph

Discussion.

Let's stop a minute. Is the Fig. 17 the same conceptual graph as the Fig. 10 ?

The answer is yes, it is. So why is there two underlying graph models ?

The distinction lies in the usage :

 A bipartite graph is easier to draw as a rounded box is easier to label than

a simple line.

 An hyper-graph is easier to code as you just have vertices and hyper-

edges. You don't have to clutter the code with two kinds of vertices.

8

A CG-tool user will usually consider CGs as bipartite graphs. Users like objects.

Users ask questions like should i use a square box or a rounded box ?

They don’t ask questions like should i use a vertex or an hyper-edge ?

So hyper-graph is a notion aimed at the CG-tool programmer.

9

Related documents

DOCX
Tourism in India: Attractions, Economic Importance, and Challenges
Tourism in India: Attractions, Economic Importance, and Challenges

1 pages

0% (0)
DOCX
The Development of Restaurants and How it has Evolved Over Time
The Development of Restaurants and How it has Evolved Over Time

7 pages

0% (0)
DOCX
Property Management Issues in the UK Hotel Industry
Property Management Issues in the UK Hotel Industry

1 pages

0% (0)
DOCX
The Rich Tapestry of Tourism in India
The Rich Tapestry of Tourism in India

1 pages

0% (0)
PDF
Tourist Trip Motivations in Digos City's Nature-Based Tourism
Tourist Trip Motivations in Digos City's Nature-Based Tourism

51 pages

0% (0)
PDF
Perceived Sociocultural Impacts of Water-Based Tourism in Matanao
Perceived Sociocultural Impacts of Water-Based Tourism in Matanao

74 pages

0% (0)
PDF
CS725 Machine Learning Lecture Notes
CS725 Machine Learning Lecture Notes

116 pages

0% (0)
PDF
Class VII Mathematics Real Numbers Notes and Practice
Class VII Mathematics Real Numbers Notes and Practice

32 pages

0% (0)
PDF
Anaerobic Digestion Processes in Wastewater Treatment
Anaerobic Digestion Processes in Wastewater Treatment

12 pages

0% (0)
PDF
Text Problems 14–17 on Nitrification and PAO Kinetics
Text Problems 14–17 on Nitrification and PAO Kinetics

6 pages

0% (0)