Extracting ontological concepts for tendering conceptual structures

It has been argued that beyond software engineering and process engineering, ontological engineering is the third capability needed if successful e-commerce is to be realized. In our experience of building an ontological-based tendering system, we face the problem of building an ontology. In this paper, we demonstrate how to build ontologies in the tendering domain. The ontology life cycle is identified. Extracting concepts from existing resources like on-line catalogs is described. We have reused electronic data interchange (EDI) to build conceptual structures in the tendering domain. An algorithm to extract abstract ontological concepts from these structures is proposed.

Conceptual structures represented by conceptual graphs and formal concept analysis

Conceptual Graphs and Formal Concept Analysis have in common basic concerns: the focus on conceptual structures, the use of diagrams for supporting communication, the orientation by Peirce's Pragmatism, and the aim of representing and processing knowledge. These concerns open rich possibilities of interplay and integration. We discuss the philosophical foundations of both disciplines, and analyze their specific qualities. Based on this analysis, we discuss some possible approaches of interplay and integration.

Lattices for 3-Dimensional Fuzzy Data generated by Fuzzy Galois Connections

Vagueness and high dimensional space data are usual features of current data. The paper is an approach to identify conceptual structures among fuzzy three dimensional data sets in order to get conceptual hierarchy. We propose a fuzzy extension of the Galois connections that allows to demonstrate an isomorphism theorem between fuzzy sets closures which is the basis for generating lattices ordered-sets

Causation and dominance : a study of Finnish causative verbs expressing social dominance

En väsentlig fråga inom såväl lingvistiska som kognitiva teorier är, hur språket beskriver kausala relationer. I finskan finns det en speciell typ av kausativa verb avledda med suffixet (U)ttA som används för att uttrycka att handlingen i fråga utförs av någon annan än subjektreferenten, t.ex. Maija haetuttaa Matilla kirjastosta kirjan ’Maija låter Matti hämta boken från biblioteket’ och Matti juoksuttaa Maijan kaupunkiin ’Matti låter Maija springa till staden’. Syftet med denna avhandling var att med exempel av sociala dominansens kausativer undersöka ordbildningens natur samt begreppet ’socialt förorsakande’. För att beskriva avledningars regelbundna argumentstruktur i form av kopplingen mellan syntaxen och semantiken upprättades deras prototypiska strukturer. Dessa verb har emellertid också specifika användningsområden som framhäver variationer i sociala relationer. Säregna egenskaper hos den sociala dominansens kausativer inkluderades i undersökningen och definierades som konstruktioner. Konstruktionerna omfattar speciella syntaktiska och/eller semantiska element och utöver det också pragmatiska värderande implikationer. Uppbyggnaden av den sociala dimensionen hos de undersökta verben består av egenskaper förbundna med typen av förorsakande, argumentens agentiva egenskaper (aktivitet eller passivitet, dominans, kontroll, viljestyrdhet och ansvarighet) samt konventionaliserade attityder och tolkningar. Ett exempel på en s.k. 'tolkningskonstruktion’ är den negativa dominansens uttryck som i avhandlingen kallas Maktmissbrukskonstruktionen. Denna konstruktion inkluderar talarens starkt kritiska hållning till den uttryckta situationen, t.ex. Asiakas juoksuttaa lentoemäntää ’Kunden låter flygvärdinnan springa’. Dessa konstruktioner fyller en viktig funktion i språklig kommunikation: att beskriva avvikande av sociala normer och att foga expressivitet till budskapet. Metodologiskt kombinerar denna avhandling teorier som baseras på det aktuella språkbruket och teoretisk lingvistisk analys. Verbens samt konstruktionernas konceptuella lexikala struktur och prototypstrukturerna analyserades med hjälp av den konceptuella semantikens verktyg, som har utvecklats av Jackendoff, Nikanne och Pörn.

Mining association rules in folksonomies

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. These systems provide currently relatively few structure. We discuss in this paper, how association rule mining can be adopted to analyze and structure folksonomies, and how the results can be used for ontology learning and supporting emergent semantics. We demonstrate our approach on a large scale dataset stemming from an online system.

BibSonomy: a social bookmark and publication sharing system

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies and briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references in a kind of personal library.

Trend detection in folksonomies

As the number of resources on the web exceeds by far the number of documents one can track, it becomes increasingly difficult to remain up to date on ones own areas of interest. The problem becomes more severe with the increasing fraction of multimedia data, from which it is difficult to extract some conceptual description of their contents. One way to overcome this problem are social bookmark tools, which are rapidly emerging on the web. In such systems, users are setting up lightweight conceptual structures called folksonomies, and overcome thus the knowledge acquisition bottleneck. As more and more people participate in the effort, the use of a common vocabulary becomes more and more stable. We present an approach for discovering topic-specific trends within folksonomies. It is based on a differential adaptation of the PageRank algorithm to the triadic hypergraph structure of a folksonomy. The approach allows for any kind of data, as it does not rely on the internal structure of the documents. In particular, this allows to consider different data types in the same analysis step. We run experiments on a large-scale real-world snapshot of a social bookmarking system.

Capturing Emergent Semantics from Social Annotation Systems

The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

Estruturação do conhecimento e relações semânticas: uma ontologia para o domínio da naonociência e nanotecnologia

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aspectos conceituais e espistemológicos do tema eletroquímica nos livros didáticos de química aprovados pelo Programa Nacional do Livro Didático para o ensino médio - PNLEM (2007)

Pós-graduação em Educação - IBRC

A arte de educar entre a mimese e o sublime: considerações a partir de Theodor W. Adorno e Jean François Lyotard

Pós-graduação em Educação - FFC