Ebook: Information Modelling and Knowledge Bases XX

In the last decades information modelling and knowledge bases have become essentially important subjects not only in academic communities related to information systems and computer science but also in the business area where information technology is applied.

The 18th European-Japanese Conference on Information Modelling and Knowledge Bases (EJC 2008) continues the series of events that originally started as a cooperation initiative between Japan and Finland, already in the last half of the 1980's. Later (1991) the geographical scope of these conferences expanded to cover the whole Europe and other countries as well.

The EJC conferences constitute a world-wide research forum for the exchange of scientific results and experiences achieved in computer science and other related disciplines using innovative methods and progressive approaches. In this way a platform has been established drawing together researches as well as practitioners dealing with information modelling and knowledge bases. The main topics of EJC conferences target the variety of themes in the domain of information modelling, conceptual analysis, multimedia knowledge bases, design and specification of information systems, multimedia information modelling, multimedia systems, ontology, software engineering, knowledge and process management. We also aim at applying new progressive theories. To this end much attention is paid also to theoretical disciplines including cognitive science, artificial intelligence, logic, linguistics and analytical philosophy.

In order to achieve EJC targets, an international program committee selected 17 full papers, 6 short papers, 7 position papers in a rigorous reviewing process from 37 submissions. The selected papers cover many areas of information modelling, namely theory of concepts, database semantics, knowledge representation, software engineering, WWW information management, multimedia information retrieval, ontological technology, image databases, temporal and spatial databases, document data management, process management, and many others.

The conference could not be a success without the effort of many people and organizations.

In the Program Committee, 31 reputable researchers devoted a good deal of effort to the review process selecting the best papers and creating the EJC 2008 program. We are very grateful to them. Professor Yasushi Kiyoki, professor Takehiro Tokuda and professor Hannu Kangassalo were acting as co-chairs of the program committee. Dr. Naofumi Yoshida and his team in Program Coordination Team were managing the review process and the conference program. Professor Xing Chen was managing the conference venue and arrangement in the organizing committee. Professor Hannu Jaakkola acted as a general organizing chair and Ms. Ulla Nevanranta as a conference secretary for general organizational things necessary for annually running the conference series. We gratefully appreciate the efforts of all the supporters.

We believe that the conference will be productive and fruitful in the advance of research and application of information modelling and knowledge bases.

The Editors

Yasushi Kiyoki, Takahiro Tokuda, Hannu Jaakkola, Xing Chen, Naofumi Yoshida

Content management is the process of handling information within an organization or community. Therefore, content management systems have to provide generic functionality for generation, extraction, storage, and exchange of digital assets. Because of the heterogeneity and complexity of content, a sufficient semantical and user-oriented annotation of content is crucial. Although semantical annotation by metadata and ontologies together with reasoning support has been extensively studied for a long time, commercially available content management systems provide only basic support for semantic modelling. Conceptual aspects of content users and support of user specific intensions are neglected. In this paper we will analyze the mismatch between the requirements of content management and semantical description and propose a data model for content which treats semantic information not only as describing metadata but incorporates the data itself, the intension behind the data, the usage of data and the origin of data on the same level.

The notion of a fragment was coined by Montague 1974 to illustrate the formal handling of certain puzzles, such as de dicto/de re, in a truth-conditional semantics for natural language. The idea of a fragment is methodological: given the vastness of a natural language, one begins with a system which is of limited data coverage, but formally explicit and functionally complete relative to a certain goal or standard.

Once a small fragment has been defined, there arises the task of upscaling, such as adding the treatment of another puzzle. Unfortunately, however, upscaling may turn out to be difficult or even impossible, depending on the assumptions of the initial fragment and the standard of functional completeness. For example, despite half a century of intensive research there is still no coherent formal account of a single natural language, verified computationally as nearly complete.

This paper proposes a new kind of fragment, called center fragment, designed to ensure the longterm success of upscaling. Its functional standard is the model of natural language communication of agent-oriented Database Semantics (DBS), based on the algorithm of time-linear LA-grammar and the data structure of proplets. Its language data are selected to represent the primary semantic relations of natural language, namely (a) functor-argument structure and (b) coordination, in their most basic form. The approach is illustrated with applications to four languages with distinctively different word orders, namely English, German, Korean, and Russian.

We introduce a new theory of concepts conceived as structured abstract entities. The theory is based on the key notion of Transparent Intensional Logic (TIL), known as TIL construction. The rich procedural semantics of TIL makes it possible to explicitly analyze all the semantically salient features of natural language expressions. We illustrate how to make use of TIL theory of concepts in distinguishing analytical and empirical concepts, and particular kinds of necessities. We also deal with a rigorous specification of requisite relations between intensions such as properties. Finally, ontology is characterised as a relatively stable part of the system that should play an integrating role. We show how to make use of TIL rich theory in specification of the content of ontologies in a multi-agent system.

In this paper we briefly describe a new conceptual model for XML called XSEM. It is a combination of several approaches in the area. It divides the conceptual modeling process to conceptual and structural level. At the conceptual level, we design an overall conceptual schema of a domain independently on the required hierarchical representations of the data in XML documents. At the structural level, we design required hierarchical representations of the modeled data in different types of XML documents. In this paper, we further extend XSEM for modeling IS-A hierarchies. We also show how conceptual XSEM schemes can be represented at the logical level in XML schemes specified in the XML Schema language.

The study of integrity constraints has been identified as one of the major challenges in XML database research. The main difficulty is finding a balance between the expressiveness and the existence of automated reasoning tools for different classes of constraints.

In this paper we define Boolean constraints for XML by exploring homomorphisms between XML data trees and XML schema graphs. These constraints are naturally exhibited by XML data due to its nested structure.

We demonstrate, in contrast to many other proposals, that reasoning about Boolean constraints is well-founded. That is, we establish that the interaction between Boolean constraints corresponds precisely to the logical implication of Boolean propositional formulae. Therefore, our Boolean constraints do not only capture valuable semantic information about XML data but also permit reasoning support by off-the-shelf SAT solvers. Finally, we identify a few subclasses of Boolean constraints for which the implication problem can be solved efficiently.

This paper presents a dynamic image-query creation and metadata extraction method with semantic correlation computation between color-combinations and impressions of multiple image data. The main features of our method are (1) to create an image-query which reflects user's intention dynamically according to the color-based combinations of images with common features selected by a user as context, (2) to extract appropriate impression by each image collection which cannot be easily extracted from a single image, (3) to provide users an image retrieval environment reflecting historical and cultural semantics and impression of color especially for cultural properties, and (4) to enable an image retrieval environment for the collection of images by time, culture, author e.t.c.. The queries are created by the combination of multiple image sets and operations, which are intersection, accumulation, average, difference of color elements of sample images. First, a set of multiple images with common features is set as sample data for a query creation. Second, color histograms are extracted from the image sets for creating feature vector of a query. Third, the correlations between an image-query vector and target image vectors are calculated on a space which represents the relationship between color and the impression according to historical and cultural semantics of color. This image-query creation method representing impression of color makes it possible to expand the range of image retrieval for a large number of image data of cultural property in digital archives, such as electronic library and electronic museum, automatically.

Peer-to-Peer (P2P) systems have been attractive solutions for resource distribution and sharing because of their self-organizing and fault-tolerant features. However, due to the decentralized nature, search efficiency is a challenging problem for large scale knowledge resource distribution P2P systems. In this paper, peer-similarity based P2P overlay clustering algorithm is proposed. Simulation results show that search efficiency using overlay clustering of similar peers is substantially improved.

Web information systems (WIS) augment classical information systems by modern Web technologies. They require at the same time a careful development and support for the interaction or story spaces beside the classical support for the working space of users. These dimensions complicate the system development process. This paper shows how classical advanced methodologies can be carefully enhanced. We evaluated the Co-Design approach to information systems development according to the ISO/IEC 15504 Framework for Process Assessment (SPICE) and derived the potential and deficiencies of this approach. This evaluation has been used for a managed Co-Design methodology. Since WIS constantly change and evolve the development process never ends. We develop as a solution an optimization procedure and a runtime environment for the Co-Design approach that allows to cope with such changes, with evolution and extension of WIS and that demonstrates the new system facilities whenever a change is mastered.

In this paper we introduce a new “scoring” description logic s-EL(D) with concept instance ordering and top-k restriction queries. This enables to create ontologies describing user preferences (ordering of concept instances) and to describe concepts consisting of top-k instances according to this ordering. We construct algorithm for instance problem in s-EL(D). The main application is an extension of web modeling languages to model user preferences and top-k in web services and web search.

Initial training, which concludes by a driving license, is insufficient because new drivers do not know how to contextualize the learned procedures into effective practices. Our goal is to improve the driver's Situation Awareness, i.e. the way in which the driver perceives events in the environment, and the projection of their status in a close future. More precisely, our concern is the way in which the driver evaluates his own competences. Our aim is to make the driver realize his drawbacks and help him to correct them. For this, first, we model drivers' behavior along two approaches, that is, local and global approaches, in order to have a driver model as exhaustive as possible. Second, we educate the driver, helping him to realize his driving's drawbacks. We present in this paper the results of a specific study on driver classification based on the two approaches.

Multi-agent system is a system of autonomous, intelligent but resource-bounded agents. Particular agents have to be able to make decisions on their own, based on the activities of the other agents and events within the system as well as its environment. Thus the agents have to communicate and collaborate with each other as well as with their environment. They communicate by exchanging messages encoded in a near-to-natural language. Traditional first-order languages are not expressive enough to meet the demands of MAS communication. Therefore we make use of the powerful system of Transparent Intensional Logic (TIL). The paper introduces the software variant of TIL, namely the TIL-Script functional programming language. We describe its syntax and semantic, as well as the way the TIL-Script facilities are integrated into the whole multi-agent system.

With the development of the Internet, Web services, such as Google Maps API and YouTube Data API, become more important and convenient for the Web knowledge distribution and integration. However, currently, most existing Web sites do not provide Web services. In this paper, we present a partial information extraction technology to construct the Web services from the general Web applications quickly and easily. Our implementation shows that our approach is applicable to different kinds of Web applications.

In this paper, we propose a news index system which supports users who would like to observe difference in various topics (e.g. politics, economy, education, and culture) among countries/regions. General news sites just provide news articles and we can only read articles which we are interested in by using a keyword search engine or selecting some topic categories provided by each site. Our system has a large index word list, a news index database, and a news directory system. The word list is constructed, expanded, and updated by collecting topic keywords from various Web sites. The news directory system consists of the word list. News articles are collected by using keyword search engines which news sites provide, then index of the collected articles is stored in the database and classified by the news directory system. We can see the difference in various topics among countries/regions by observing co-occurrence of two or more words in the word list.

The architecture of participation and sharing that encourage users to add value is one of the fundamental characteristics of a successful Web 2.0 application. Blog, as a personal publish platform on the web, removes the intermediation for channel selection thus everyone can represent himself/herself without any filtering mechanism. In this research, we present a methodology to derive user's degree of expertise from blog data and conduct an experiment using data collected from a enterprise blog system. The result shows that the average precision reaches around 0.8 and which factor is useful in our proposed method.

This paper presents a novel model of co-reference knowledge, which is based on the distinction of (i) a model of a common reality, (ii) a model of an agent's opinion about reality, and (iii) a model of agents' opinions if they talk about the same object or not. Thereby it is for the first time possible to describe consistently the evolution of the agent's knowledge and its relative consistency, and to formally study algorithms for managing co-reference knowledge between multiple agents if they have the potential to lead to higher states of consistency, independent from the particular mechanism to recognize co-reference. As an example, a scalable algorithm is presented based on monitoring atomic knowledge increments and an abstract notion of belief ranking. The presented approach has a wide potential to study the formal properties of current methods to find co-reference, and to lead to new methods for the global management of co-reference knowledge.

This paper discusses whether relationships can preferably be reduced to properties in conceptual modelling and formal ontology engineering. The discussion takes as point of departure the subject-predicate form of logic supporting a monadistic view.

This paper presents a multiple knowledge spaces creation process for domain oriented semantic associative search. We have presented a generation method of semantic associative search spaces for domain-specific research areas. This process enables database managers and experts of the specific domain to collaborate in constructing semantic search spaces with domain-oriented knowledge. Domain-specific knowledge space creation is essentially important to obtain appropriate knowledge from expert-level document repositories. This paper presents the implementation process for knowledge space creation and the software environment for supporting collaboration work between database managers and domain experts.

In the paper we propose a Brain Architecture which allows developers of a Multi-Agent System (MAS) to integrate various supporting tools. For the purpose of agents' communication and reasoning we make use of Transparent Intesional logic (TIL), or more exactly of its software variant the TIL-Script language. The proposed architecture makes it possible to utilise also the Prolog language as a reasoning tool. Rules and facts are stored in agent's internal knowledge base is designed in a way appropriate both for Prolog and TIL-Script languages. The architecture is an open one so that other tools of reasoning can be easily incorporated.

This paper presents an implementation method of a meta-level knowledge base system for analyzing personal career opportunities by connecting occupational and educational databases. We have designed and implemented several functions to analyze information on personal career development, on the meta-level database system for connecting occupational and educational databases. This method is used to create dynamic relationships among heterogeneous databases on occupations, educational contents, social and educational issues and personal career information. In this method, several functions are defined for analyzing relationships among heterogeneous databases. (1) Educational contents represent, for instance, lectures in educational institutes, (2) occupations represent descriptions of concrete occupations, (3) social and educational issues represent academic industrial fields, and (4) personal career information represents histories, objectives and interests of an individual user's career. These databases are connected and analyzed in a dynamic way, according to users' contexts and situations. By using our method, individual career development becomes to be effectively supported when discovering personal career opportunities and designing personalized career development plans.

Time is an essential dimension in our knowledge space. Understanding different temporal dimensions and dynamics in cross-cultural meetings and negotiation processes will improve our skills in cross-cultural communication and increase our cultural competence. It also helps us to identify and formalize cross-cultural concepts and related temporal entities and to construct for example cross-cultural XML Schemas. We address three issues in our paper. First, we discuss implications of cross-cultural differences for meetings and negotiations and introduce the concept of a temporal entity in this context. Second, we present three relevant ontological approaches – OWL-Time, temporal aggregates and temporal regions of the Span ontology – for modelling temporal entities in the context of cross-cultural meetings and negotiations. Third, we give proof-of-concept examples of applying those ontological approaches to scheduling meetings and recurrent actions over time zones and to describing temporal parts of cross-cultural meetings and negotiations between Finland and Japan. Cross-cultural XML Schemas and temporal entities have important roles in design and implementation of culture-sensitive information systems.

In this paper we discuss models of formal argumentation games. We argue that the tactics and strategies of board-games like chess provide a useful analogy for adversarial argumentation games. The objective of this study is to elaborate on a common model for board games and argumentation dialogues. In particular we strive at making analogies between tactical and strategic chess game notions and notions in adversarial argumentation games.

Various authors in the field of knowledge management have adopted the view that individuals' tacit knowledge should be externalized and shared in organizations. According to Polanyi's original theory of tacit knowing, an explicit expression of tacit knowledge is, however, considered very difficult, even impossible. We studied this contradiction by analyzing Polanyi's theory of tacit knowing in order to consider the correctness of the idea of externalization of tacit knowledge. Despite the fact that tacit knowing is an essential basis for all knowledge, we claim that tacit knowledge cannot be externalized in a way it is presented in the knowledge management literature.

The article presents results of an international project in the semantic approach to the information system development in security area. The aim of the project is the verification of semantic possibilities based on commercial software. The thesauri design and verification using document base and analytical SW is described, as well as UML applied to an ontology modelling. An ontology was implemented in ITM and IS was verified.

This paper demonstrates how cognitive psychology can contribute to the development of ontologies for semantic technologies and the semantic web. Specifically, the way in which the human cognitive system structures and processes conceptual information can act as a model for structuring formal ontologies, and can guide knowledge elicitation and the use of controlled natural languages. One conclusion is that during knowledge elicitation the dynamic nature of human information retrieval needs to be taken into account to obtain an ontology that is appropriate for its context of use. A further practical implication is that ontology developers need to be more specific and explicit about what they mean by the term ontology (e.g. does an ontology describe typical concept attributes or attributes that are true of most instances?) when explaining the use of concepts in ontologies to domain experts.

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