Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We shall use the generic term information systems, in its broadest sense, to collectively refer to these application perspectives. We argue in this paper that so-called ontologies present their own methodological and architectural peculiarities: on the methodological side, their main peculiarity is the adoption of a highly interdisciplinary approach, while on the architectural side the most interesting aspect is the centrality of the role they can play in an information system, leading to the perspective of ontology-driven information systems.

We present a new approach to extracting information from unstructured documents based on an application ontology that describes a domain of interest. Starting with such an ontology, we formulate rules to extract constants and context keywords from unstructured documents. For each unstructured document of interest, we extract its constants and keywords and apply a recognizer to organize extracted constants as attribute values of tuples in a generated database schema. To make our approach general, we fix all the processes and change only the ontological description for a different application domain. In experiments we conducted on two different types of unstructured documents taken from the Web, our approach attained recall ratios in the 80 % and 90 % range and precision ratios near 98%.

This paper describes the formalization effort of different sets of object-oriented metrics definitions using the Object Constraint Language (OCL), a part of the Unified Modeling Language (UML) standard. The formalization is based upon the UML meta-model. This approach allows unambiguous metrics definition, which in turn helps increasing tool support for Object-Oriented metrics. Also, it is possible to establish comparisons among the formalized sets of metrics.

Database design commonly assumes, explicitly or implicitly, that instances must belong to classes. This can be termed the assumption of inherent classification. We argue that the extent and complexity of problems in schema integration, schema evolution, and interoperability are, to a large extent, consequences of inherent classification. Furthermore, we make the case that the assumption of inherent classification violates philosophical and cognitive guidelines on classification and is, therefore, inappropriate in view of the role of data modeling in representing knowledge about application domains. As an alternative, we propose a layered appro...

Automatically recognizing which Web documents are “of interest ” for some specified application is non-trivial. As a step toward solving this problem, we propose a technique for recognizing which multiple-record Web documents apply to an ontologically specified application. Given the values and kinds of values recognized by an ontological specification in an unstructured Web document, we apply three heuristics: (1) a density heuristic that measures the percent of the document that appears to apply to an application ontology, (2) an expected-value heuristic that compares the number and kind of values found in a document to the number and kind expected by the application ontology, and (3) a grouping heuristic that considers whether the values of the document appear to be grouped as application-ontology records. Then, based on machine-learned rules over these heuristic measurements, we determine whether a Web document is applicable for a given ontology. Our experimental results show that we have been able to achieve over 90 % for both recall and precision, with an Fmeasure of about 95%. 1

We propose to standardize object-oriented metrics definitions using the Object Constraint Language (OCL), a part of the Unified Modeling Language (UML) standard, and a meta-model of the modeling formalism. OCL allows specifying invariants, preconditions, postconditions and other types of constraints. To illustrate this approach, we describe the MOOD2 metrics in OCL, based upon the meta-model of our object design modeling formalism – the GOODLY language. The outcome is, we believe, an elegant, precise and straightforward way to define metrics that may help to overcome several current problems. Besides, it is a natural approach since we are using object technology to define metrics on object technology itself. 1.

Object-oriented computing is influencing many areas of computer science including software engineering, user interfaces, operating systems, programming languages and database systems. The appeal of object-orientation is attributed to its higher levels of abstraction for modeling real world concepts, its support for incremental development and its potential for interoperability. Despite many advances, object-oriented computing is still in its infancy and a universally acceptable definition of an object-oriented data model is virtually nonexistent, although some standardization efforts are underway. This report presents the TIGUKAT 1 object model definition that is the result of an investigation of object-oriented modeling features which are common among earlier proposals, along with some distinctive qualities that extend the power and expressibility of this model beyond others. The literature recognizes two perspectives of an object model: the structural view and the behavioral view. ...

Programming is a modeling process where phenomena and abstractions from a referent system are expressed using a programming language. To improve the efficiency of program development, programming languages should be designed to reflect human conceptualization as well as possible. This will make programs easier to comprehend, thus aiding during both development and maintenance, and it will aid in making the developed programs conform better to the users expectations. This paper will present a model of the interactions between epistemology, concept formation, programming language analysis and design, and programming. The model will be used to develop a taxonomic framework for analyzing and designing abstraction mechanisms found in object-oriented languages. keywords: object oriented modeling, language design, language comparision, programming paradigms 1 Introduction This paper is an attempt to define and illustrate an approach to programming which we call conceptual programming. The m...

This paper discusses the formalization effort of object-oriented design metrics definitions and presents some concrete examples, developed upon the UML meta-model. The Object Constraint Language (OCL), a part of the Unified Modeling Language (UML) standard, is used in the formalization. The combination of the UML meta-model and OCL allows unambiguous metrics definition, which in turn helps increasing tool support for object-oriented metrics extraction. This formalization renders possible the comparisons among different sets of metrics, as well as it may be used to establish a common vocabulary among different stakeholders. As consequence, the precision of the metrics collection increases, contributing to the overall quality of the Software Engineering process.

Knowledge management research focuses on the development of concepts, methods, and tools supporting the management of human knowledge. The main objective of this paper is to survey some of the basic concepts that have been used in computer science for the representation of knowledge and summarize some of their advantages and drawbacks. A secondary objective is to relate these techniques to information sciences theory and practice. The survey classifies the concepts used for knowledge representation into four broad ontological categories. Static ontology describes static aspects of the world, i.e., what things exist, their attributes and relationships. A dynamic ontology, on the other hand, describes the changing aspects of the world in terms of states, state transitions and processes. Intentional ontology encompasses the world of things agents believe in, want, prove or disprove, and argue about. Social ontology covers social settings, agents, positions, roles, authority, permanent org...