Wojciech Waloszek

The cartographer algorithm for processing and querying description logics ontologies

One of the most popular formalisms of describing knowledge is Description Logics. It has become even more popular when OWL standard has emerged. The paper presents a new reasoning algorithm – the Cartographer Algorithm – that allows for inferring implicit knowledge from a terminology (TBox) and assertions (ABox) of an ontology. The paper describes the way of processing ontologies in terms of binary signatures and an efficient way of querying ontologies containing numerous individuals. In addition, results of experiments comparing the Cartographer Algorithm with other reasoners are presented.

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.

The knowledge cartography – a new approach to reasoning over description logics ontologies

The paper presents a new method for representation and processing ontological knowledge – Knowledge Cartography. This method allows for inferring implicit knowledge from both: terminological part (TBox) and assertional part (ABox) of a Description Logic ontology. The paper describes basics of the method and gives some theoretical background of the method. Knowledge Cartography stores and processes ontologies in terms of binary signatures, which gives efficient way of querying ontologies containing numerous individuals. Knowledge Cartography has been applied in KaSeA – a knowledge management system that is being developed in course of a European integrated research project called PIPS. Results of efficiency experiments and ideas of further development of the system are presented and discussed.

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.

Processing and Querying Description Logic Ontologies Using Cartographic Approach

Description Logic (DL) is a formalism for knowledge representation that recently has gained widespread recognition among knowledge engineers. After a brief introduction to DL, the paper presents a DL reasoner developed at Gdansk University of Technology (GUT). The reasoner, called KaSeA, is based on an original idea called Knowledge Cartography. The paper presents basics of Knowledge Cartography, its potentials and limitations, and compares the solution with other DL reasoners.

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.

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.

The Algorithm of Modelling and Analysis of Latent Semantic Relations: Linear Algebra vs. Probabilistic Topic Models

This paper presents the algorithm of modelling and analysis of Latent Semantic Relations inside the argumentative type of documents collection. The novelty of the algorithm consists in using a systematic approach: in the combination of the probabilistic Latent Dirichlet Allocation (LDA) and Linear Algebra based Latent Semantic Analysis (LSA) methods; in considering each document as a complex of topics, defined on the basis of separate analysis of the particular paragraphs. The algorithm contains the following stages: modelling and analysis of Latent Semantic Relations consistently on LDA- and LSA-based levels; rules-based adjustment of the results of the two levels of analysis. The verification of the proposed algorithm for subjectively positive and negative Polish-language film reviews corpuses was conducted. The level of the recall rate and precision indicator, as a result of case study, allowed to draw the conclusions about the effectiveness of the proposed algorithm.