Abstract. This paper develops
two agent knowledge bases in conceptual graph form, one using the KD45
underlying logical model for belief and one without any underlying
logical model for belief. Action-attitudes in the knowledge
bases provide contexts that represent the agents’ mental attitude
towards, and willingness to act upon information in the knowledge bases.
Preconditions for communication acts are also represented in the knowledge
bases as well as mental attitude changes following communications.
Conceptual graphs are a flexible and extendable form of knowledge representation
that is used to capture and represent semantic constituents of communications
in a form that may be used by software agents. The knowledge base representations
in this paper provide software agents a perspective from which they
may reason about the communicating agent’s beliefs and
communication actions
Abstract: This paper outlines a vision for using
conceptual graphs to build active knowledge systems that have the
capability to solve practical and com-plex problems. A key ingredient
in an active knowledge system is its ability to interact (not just
interface) with the real world. Basic features of such systems go
beyond logic to include support for data mining, intelligent agents,
temporal actors, active sensors, a system for knowledge interchange
and finally, support for knowledge-in-the-large
Abstract. Agent communication languages such as KQML and the FIPA ACL
serve as metalanguages to define software agent message-passing protocols.
These metalanguages are incompatible with each other, preventing intercommunication
between agents employing different agent communication languages. The
primary hindrance to agent intercommunication is the different underlying
semantics of the message passing protocols. Conceptual graphs provide
a mechanism to bridge this agent communication barrier by representing
the semantics of message-passing protocols in the formal representation
of conceptual graphs. Semantic content of the KQML tell performative
is contrasted with that of the FIPA ACL inform performative and represented
in conceptual graphs. The intent is that software agents conversant in
CGIF may intelligently translate messages between agents employing different
agent communication languages.
Abstract: Analysis of dependencies between entities
is an important part of modeling. Whether the modeling domain is at
the enterprise level or at the system or software component level,
characterization, representation, and analysis of these dependencies
is essential to correctly modeling the domain. For example, it is important
to identify and characterize dependencies between both system and software
components when trying to determine the extent of and impact of a breach
in computer system security or of a malfunction in a component. Analysis
of such dependencies is also greatly beneficial in both the requirements
and maintenance phases of software engineering. What is needed is a
formal characterization of the concept of dependency along with a more
formal and unified approach to dependency analysis . This paper introduces
the notion of dependency at a general level. In the present literature,
an actual definition and characterization of a dependency is usually
avoided, and it is difficult to separate the discussion of the dependency
from the particular domain of interest. Most of the literature available
implies that it is simply “understood” that a dependency
can be represented by a directed arc on a graph where the dependent
components are the nodes of the graph. Much work in the current literature
addresses dependencies in widely varying ways. This paper attempts
to formalize both the definition and characterization of a dependency
in a unified approach, and then illustrates how dependencies themselves
and the effect of those dependencies upon a system can be efficiently
modeled using Conceptual Graphs.
Abstract: A knowledge acquisition technique called Troika is
presented. Based on a combination of repertory grids, conceptual graphs
and formal concept analysis, Troika is a hybrid approach that combines
these three approaches. The approaches are introduced and their strengths
summarized. Troika's basic algorithms are presented. Some samples from
an actual acquisition process are presented to provide some flavor
of the approach.
Abstract: In recent years much work has been
performed in developing suites of metrics that are targeted for object-oriented
software, rather than functionally-oriented software. This is necessary
since good object-oriented software has several characteristics, such
as inheritance and polymorphism, that are not usually present in functionally-oriennted
software. However, all of these object-oriented metrics suites have
been defined using only syntactic aspects of object-oriented software;
indeed,
the earlier functionally-oriented metrics were also calculated using
onlysyntactic information. All syntactically-oriented metrics have
the problem that the mapping from the metric to the quality the metric
purposrts
to measure, such as the software quality factor "cohesion," is
indirect, and often arguable. Thus, a substantial amount of research
effort goes into proving that these syntactically-oriented metrics
actually do measure their associated quality factors. This paper introduces
a
new suite of semantically-derived object-oriented mmetrics, which provide
a mor e direct mapping from the metric to its associated quality factor
than is possible using syntactic metrics. These semantically-derived
metrics are calcualted using knowledge-based, program understanding,
and natural langauge processing techniques.
- Abstract: The purpose of this paper is to introduce an approach
to conceptual modeling and acquisition that combines useful features
from two well-known knowledge representations: repertory grids and
conceptual graphs. Conceptual graphs have the expressive power and
reasoning support needed for an effective knowledge-based system, while
repertory grids have the cognitive/psychological basis and generality
needed to provide excellent elicitation and acquisition facilities.
This hybrid approach lends itself to several knowledge acquisition
methods, such as using conceptual graphs to build repertory grids,
using repertory grids to build conceptual graphs, and using them together
to perform heuristic classification. The paper shows how each representation,
with only minor adaptation, can accommodate "hooks" into
the other so that each may exploit the power of the other in providing
efficient knowledge elicitation and acquisition support.
- Abstract: A multiple viewed requirements technique deals with
requirements analysis based on having available diverse multiple descriptions
of software requirements. Because these multiple descriptions are often
expressed in differing notation schemes based on differing underlying
paradigms and methodologies, the problem of consistency and completeness
is a significant impediment to obtaining a reliable set of requirements.
This paper outlines part of an approach to these multiple-viewed requirements
that provides some structure for integrating and validating multiple
views. The approach, based on conceptual graphs as a knowledge representation,
provides a general and flexible framework within which to acquire and
analyze multiple views. As views are acquired, each developer can obtain
feedback from others' views within his original notation and thereby
gain new insight into his own view.
- Abstract: Construction of complex systems requires an understanding
of the relation between the problem domain, the problem, and the problem-solving
method. Presently, knowledge acquisition systems display limited versatility.
By integrating repertory grids with conceptual graphs, an improved
ability to handle the problem domain, the problem, and the problem-solving
method is attained. Repertory grids may be interfaced with conceptual
graphs by translating the meaning of repertory grid constructs into
conceptual graphs. A robust translation method is presented along with
a demonstrative example of the application of the method to repertory
grids. This example suggests the utility of the technique in integrating
knowledge from multiple experts.
- Abstract: Relational databases are in widespread use, yet
they suffer from serious limitations when one uses them for reasoning
about real-world enterprises. This is due to the fact that database
relations possess no inherent semantics. This paper describes an approach
called microanalysis that we have used to effectively capture
database semantics represented by conceptual graphs. The technique
prescribes a manual knowledge acquisition process whereby each relation
schema is captured in a single conceptual graph. The schema's graph
can then easily be instantiated for each tuple in the database forming
a set of graphs representing the entire database's semantics. Although
our technique originally was developed to capture semantics in a restricted
domain of interest, namely database inference detection, we believe
that domain-directed microanalysis is a general approach that can be
of significant value for databases in many domains. We describe the
approach and give a brief example.
- Abstract: This paper presents a model of database inference
and a taxonomy of inference detection approaches. The Merlin inference
detection system is presented as an example of an automated inference
analysis tool that can assess inference vulnerabilities using the schema
of a relational database. A manual inference penetration approach is
then offered as a means of detecting inferences that involve instances
of data or characteristics of groups of instances. These two approaches
are offered as practical approaches that can be applied today to address
the database inference problem. The final section discusses future
directions in database inference research.
- Abstract: The database inference problem is a well-known problem
in database security and information system security in general. In
order to prevent an adversary from inferring classified information
from combinations of unclassified information, a database inference
analyst must be able to detect and prevent possible inferences. Detecting
database inference problems at database design time provides great
power in reducing problems over the lifetime of a database. We have
developed and constructed a system called Wizard to analyze databases
for their inference problems. The system takes as input a database
schema, its constituent instances (if available) and additional human-supplied
domain information, and provides a set of associations between entities
and/or activities that can be grouped by their potential severity of
inference vulnerability. A knowledge acquisition process called microanalysis
permits semantic knowledge of a database to be incorporated into the
analysis using conceptual graphs. These graphs are then analyzed with
respect to inference-relevant domains we call facets using tools we
have developed. We can determine inference problems within single facets
as well as some inference problems between two or more facets. The
architecture of the system is meant to be general so that further refinements
of inference information subdomains can be easily incorporated into
the system.
- Abstract: This paper describes an approach to database inference
analysis based on conceptual graphs. The database inference problem
is briefly described. Previous approaches are summarized, followed
by a presentation of our inference model, called AERIE. The notions
of an inference target class and an inference method class are introduced
with examples given. Conceptual graphs are introduced as our means
of representing database inference knowledge, as a first step toward
analyzing and detecting database inference problems. The classification
of inference target classes and the use of conceptual graphs for database
inference detection are two important contributions of this paper.
Four examples are used to illustrate the approach. We discuss some
interesting issues raised by this work, and offer conclusions and our
plans for future research.
- Abstract: This paper describes an application of conceptual
graphs to support software requirements development -- the process
of determining what software needs exist and how those needs will be
filled. As a human knowledge- and experience-based activity, requirements
development is an appropriate domain for applying formal models of
cognitive structures. This chapter introduces the following contributions
to the theory and practice in conceptual graphs: (a) the ability to
represent a conceptual graph that changes over time, using a new class
of node called a demon node. (b) a structure to partially manipulate
informal (external) information (i.e., information not expressed in
conceptual graphs), by introducing a special referent form called a
private referent. (c) the ability to obtain a conceptual graph representation
from a requirements specification written in one of several common
notations. (d) a framework using conceptual graphs in the analysis
of software requirements that effectively captures the overlap between
multiple views.
- Abstract: Conceptual graphs support a notion called a ``line
of identity'' (also called a ``co-referent link'') that specifies a
single concept which is denoted by two or more concept boxes. The multiple
concepts can be joined into a single concept (if they are in the same
context). This work proposes a richer notion, expressible using existing
conceptual graph constructs, that allows finer distinctions to be made
about what concepts are allowed to be joined, and also addresses the
problem of joining between different contexts. In the course of describing
an entire relational database with multiple graphs (one for each database
relation). We encountered a problem in joining these graphs into one
large graph (the universal join relation); namely, the existence of
some instance constraints on joins. In some cases, foreign key attributes
in one relation's graph cannot be joined unconditionally with their
corresponding attributes in another relation. We describe a new notion,
a conditional join, to handle this problem and others as well. We provide
a rationale, description and examples of such a join.
- Abstract: Conceptual graphs are applied to a problem in database
inference known as second path analysis. A sensitive target is proposed,
namely to keep secret that a certain company is working on a certain
project. Typically available non-sensitive information is introduced
in the form of relational database schemata. These schemata are then
expressed as conceptual graphs, followed by a series of joins which
are performed revealing the sensitive target. It is shown that conceptual
graph representations are able to analyze second path problems and
achieve the same results as previous techniques. A new inference path
was discovered that had not been identified by previous work.
- Abstract: Conceptual graphs have been used to model information
in many complex domains, but the domain of economics is particularly
difficult because its knowledge is based as much on perceptions of
people as on physical laws. This paper addresses that problem using
as a vehicle one well-known basic economic area: namely, the law of
supply and demand. Employing Peirce logic negative contexts, we represent
various parts of classical economic theory, e.g., over-supply, over-
demand, and equilibrium states. It is shown how tacit knowledge is
relevant to the modeling of this information, and why this knowledge
requires the conceptual graphs to be built and reviewed by the domain
experts directly. Conceptual graph actors are employed to represent
relationships between quantities and to represent market forces. Negative
contexts are briefly evaluated as a modeling tool. Representing changes
in domain assumptions is discussed.
- Abstract: Among all the phases of software development, requirements
are particularly difficult to specify and analyze, since requirements
for any large software system originate with many different persons.
Each person's view of the software requirements may be expressed in
a different notation, based on that person's knowledge, experience,
and vocabulary. In order to perform a knowledge-based analysis of the
requirements in combination, a single knowledge representation must
be capable of capturing the information expressible in several existing
requirements notations. This paper introduces the notation of conceptual
graphs based on semantic networks, that provides a general representation.
Four common requirements notations are shown to be expressible using
conceptual graphs; with algorithms and examples provided.
- Abstract: Secure databases are ones in which classified information
is protected from access by unauthorized persons. Although the information
itself may be secure from direct access, data within the database may
be combined along with external data to permit classified data to be
inferred. This problem, called the {\em database inference problem},
can be addressed by analyzing a database and its design. An inference
detection model based on conceptual graphs is introduced, and explained
in terms of different kinds of inference that may be performed. An
automated inference analysis tool (IAT) is introduced and its overall
architecture described.
- Abstract: The issue of semantic distance has been discussed
in several previous papers. Various strategies have been proposed for
obtaining some quantitative measure of the similarity between things.
In conceptual graph terms, the various approac hes may often be classified
according to operations involving the type hierarchy, canonical graph
definitions and the context in which particular concepts are found.
The proposed paper will discuss the following topics: (a) The meaning
of semantic distance, (b) Issues regarding semantic distance measures,
(c) Taxonomy of semantic distance measurement schemes, and (d) How
to conduct an empirical study of intuitive semantic distance. The purpose
of this paper is to suggest an approach for incorporating the notion
of semantic distance into the conceptual graph theory, while preserving
its meaning as already studied by psychologists, philosophers and cognitive
scientists.
- Abstract: This paper proposes an extension to conceptual graphs
that captures dynamic aspects of knowledge. This extension is necessary
because some kinds of temporal notions are not effectively represented
in conceptual graphs containing only concepts, relations and actors.
A fundamental extension to conceptual graphs is needed that captures
the temporal idea of a process or transformation. A new conceptual
graph node type called a demon is proposed, its semantics presented
in terms of its relationship to other temporal logics. Examples are
provided.
- Abstract:
Most current software requirements development methods center
around a single view to which all requirements are made to fit.
Such methods are insufficient for requirements that may fall outside
the given model, furthermore, they do not take into account important
underlying assumptions of the participants. Recent approaches have
acknowledged the need for accommodating multiple views of software
requirements; however, these approaches have little formal basis
with which to perform analysis of the combined requirements. They
rely instead on the skill and experience of a human requirements
analyst for their effectiveness.
This thesis introduces a knowledge representation approach to
multiple viewed software requirements. Using its methodology, participants
are free to choose any model they desire for expressing their particular
requirements. Each participant's requirements specification is
then translated in one common meta-language upon which analysis
is performed. The methodology can lead to identification of common
elements between the views as well as ambiguities in the views'
combination of requirements.
The requirements analyst uses the knowledge representation of
conceptual graphs as a meta-language to capture the knowledge from
several participants' views. Each set of requirements is then manipulated
in graph form to determine the common concepts, called counterparts,
between two or more views. The separate graphs can also be combined
to form one set of requirements for the entire system.
The combination technique employs an association graph whereby
each possible set of counterparts is weighted according to its
types and its relationships to other possible counterparts in the
requirements. Refinements to the technique take into account a
pre-existing general knowledge base. As a result, a numerical comparison
is achieved, identifying the strongest possible counterparts and
identifying possibly ambiguous counterparts that must be distinguished
by feedback from the participants, resulting in additional assumptions,
refined requirements, and a further iteration of the methdology.
The thesis also offers a validation framework which can be used
to measure the improvements offered by this approach to overall
system requirements, and provides a brief example to illustrate
the methodology.
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