Aleksander Waloszek

Algebra of Ontology Modules for Semantic Agents

In the environment of Semantic Web the problem of precise manipulation of units of knowledge gains importance. In this paper we discuss a possibility of adoption for this purpose the flexible and powerful apparatus of relational algebra. We discuss similarities and differences between knowledge and data bases and their underlying information-processing models. On the basis of the discussion we draw and investigate a special analogy between these two important methods. We use this analogy to introduce the special algebra of ontological modules which may be used to exchange, align and merge the knowledge among agents.

Terminological and assertional queries in KQL knowledge access language

One of the directions of development of information systems in recent years is the evolution of data-based systems into the knowledge-based systems. As a part of this process there is ongoing work on a whole range of languages for accessing knowledge bases. They can be used in a variety of applications, however their main drawback is the lack of clearly defined algebra representing a theoretical basis for them. For instance, such a basis is the relational algebra for SQL. The paper presents a new language for accessing knowledge bases that is built on a solid, theoretical foundation - the algebra of ontological modules.

Modularized Knowledge Bases Using Contexts, Conglomerates and a Query Language

The paper presents a novel approach to design and development of a modularized knowledge base. It is assumed that the knowledge base consists of a terminology (axioms) and a world description (assertions), both formulated in a Description Logics (DL) dialect. The approach is oriented towards decomposition of a knowledge base into logical components called contexts and further into semantic components called conglomerates. Both notions were elaborated separately elsewhere. The paper shows how contexts and conglomerates concepts can work in harmony to create a maintainable knowledge base. An architecture of a system that conforms to this approach, which additionally uses a query language called KQL (Knowledge Query Language), is presented. The approach is intended to be used to build a prototypical system that aims at integrating knowledge on cultural heritage coming from digital libraries, including user-defined libraries. The thorough discussion of related work is also given.

Theoretical and Architectural Framework for Contextual Modular Knowledge Bases

The paper presents the approach aimed at building modularized knowledge bases in a systematic, context-aware way. The paper focuses on logical modeling of such knowledge bases, including an underlying SIM metamodel. The architecture of a comprehensive set of tools for knowledgebase systems engineering is presented. The tools enable an engineer to design, create and edit a knowledge base schema according to a novel context approach presented elsewhere by the authors. It is explained how a knowledge base built according to SIM (Structured-Interpretation Model) paradigm is processed by a prototypical reasoner Conglo-S, which is a custom version of widely known Pellet reasoner extended with support for modules of ontologies called tarsets (also introduced elsewhere under the name of conglomerates). The user interface of the system is a plug-in to Protege ontology editor that is a standard tool for development of Semantic Web ontologies. Possible applications of the presented framework to development of knowledge bases for culture heritage and scientific information dissemination are also discussed.

A distributed description of facts in a distributed Semantic Web ontology

During the development of semantic Web there emerged a need for creating semantic descriptions of large domains of interest. However, it turned out that the large size of ontologies containing such descriptions led to many negative effects. As a result, the topics of distributing ontologies and ontology modularization gained major importance. The purpose of this paper is to present a novel approach to describe semantics of modules in distributed ontologies. We categorize problems that are encountered while working with ontology modules and describe some of the best known methods of importing data from a source ontology to a target one. Then we describe our contextual framework that generalizes our approach to the contextualization. This framework introduces a hierarchy of contexts accompanied by a hierarchy of context instances. We show how such a structure helps to solve some crucial problems with modularization, like constraining visibility and avoiding inconsistencies or incoherencies.

Extending Expressiveness of Knowledge Description with Contextual Approach

In the paper we show how imposing the contextual structure of a knowledge base can lead to extending its expressiveness without changing the underlying language. We show this using the example of Description Logics, which constitutes a base for a range of dialects for expressing knowledge in ontologies (including state-of-the-art OWL).

SACAM - A Model for Describing and Classifying Sentiment Analysis Methods.

In this paper we introduce SACAM — a model for describing and classifying sentiment analysis (SA) methods. The model focuses on the knowledge used during processing textual opinions. SACAM was designed to create informative descriptions of SA methods (or classes of SA methods) and is strongly integrated with its accompanying graphical notation suited for presenting the descriptions in diagrammatical form. The paper discusses applications of SACAM and shows directions of its further development.

Contextual approach to reasoning with rules

In the paper we present a method of reasoning with Horn rules within a contextual framework. We show that by proper use of a structure of contexts we can obtain partial OWA compliance with no necessity of extending the syntax of underlying Description Logics.

Reasoning with Projection in Multimodular Description Logics Knowledge Bases

We present an approach to reasoning with projection, i.e. reasoning in which it is possible to focus on a selected part of knowledge (by neglecting some non-interesting fragments). Projection is most useful for modular knowledge bases in which only parts of knowledge have to be exchanged or imported to other modules. In this paper we present an optimized method of reasoning over results of projection. The tests indicate that the method can drastically reduce the time of inferencing, enabling our reasoner to efficiently work with modular knowledge bases embracing several dozens of modules, even in the presence of cyclic interrelationships between them.

Contextualizing a Knowledge Base by Approximation - A Case Study

Modular knowledge bases give their users opportunity to store and access knowledge at different levels of generality. In this paper we present how to organize a modular knowledge bases organized into contexts in which a user can express their knowledge in much simplified way, yet without losing its precision. The work is centered around the notion of approximation - i.e. reducing the arity of predicates used. The presentation is based on a case-study conducted with CongloS system within a large-scale national project.