Aligning Controlled vocabularies for enabling semantic matching in a distributed knowledge management system

The underlying idea of the Semantic Web is that web content should be expressed not only in natural language but also in a language that can be unambiguously understood, interpreted and used by software agents, thus permitting them to find, share and integrate information more easily. The central notion of the Semantic Web's syntax are ontologies, shared vocabularies providing taxonomies of concepts, objects and relationships between them, which describe particular domains of knowledge. A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred to as the Controlled Vocabulary (CV) if choice or selection of terms are done by domain specialists. A facet is a distinct and dimensional feature of a concept or a term that allows a taxonomy, ontology or CV to be viewed or ordered in multiple ways, rather than in a single way. The facet is clearly defined, mutually exclusive, and composed of collectively exhaustive properties or characteristics of a domain. For example, a collection of rice might be represented using a name facet, place facet etc. This thesis presents a methodology for producing mappings between Controlled Vocabularies, based on a technique called \Hidden Semantic Matching". The \Hidden" word stands for it not relying on any sort of externally provided background knowledge. The sole exploited knowledge comes from the \semantic context" of the same CVs which are being matched. We build a facet for each concept of these CVs, considering more general concepts (broader terms), less general concepts (narrow terms) or related concepts (related terms).Together these form a concept facet (CF) which is then used to boost the matching process

Annotation-based storage and retrieval of models and simulation descriptions in computational biology

This work aimed at enhancing reuse of computational biology models by identifying and formalizing relevant meta-information. One type of meta-information investigated in this thesis is experiment-related meta-information attached to a model, which is necessary to accurately recreate simulations. The main results are: a detailed concept for model annotation, a proposed format for the encoding of simulation experiment setups, a storage solution for standardized model representations and the development of a retrieval concept.Die vorliegende Arbeit widmete sich der besseren Wiederverwendung biologischer Simulationsmodelle. Ziele waren die Identifikation und Formalisierung relevanter Modell-Meta-Informationen, sowie die Entwicklung geeigneter Modellspeicherungs- und Modellretrieval-Konzepte. Wichtigste Ergebnisse der Arbeit sind ein detailliertes Modellannotationskonzept, ein Formatvorschlag für standardisierte Kodierung von Simulationsexperimenten in XML, eine Speicherlösung für Modellrepräsentationen sowie ein Retrieval-Konzept

An Application of Collaborative Web Browsing Based on Ontology Learning from User Activities on the Web

With explosively increasing amount of information on the Web, users have been getting more bored to seek relevant information. Several studies have introduced adaptive approaches to recognizing personal interests. This paper proposes the collaborative Web browsing system that can support users to share knowledge with other users. Especially, we have focused on user interests extracted from their own activities related to bookmarks. A simple URL based bookmark is provided with semantic and structural information by the conceptualization based on ontology. In order to deal with the dynamic usage of bookmarks, ontology learning based on a hierarchical clustering method can be exploited. As a result of our experiments, about 53.1 % of the total time was saved during collaborative browsing for seeking the equivalent set of information, compared with single Web browsing. Finally, we demonstrate implementing an application of collaborative browsing system through sharing bookmark-associated activities

Semantic enrichment of knowledge sources supported by domain ontologies

This thesis introduces a novel conceptual framework to support the creation of knowledge representations based on enriched Semantic Vectors, using the classical vector space model approach extended with ontological support. One of the primary research challenges addressed here relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. This research explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents. The relevant achievements pursued by this thesis are the following: (i) conceptualization of a model that enables the semantic enrichment of knowledge sources supported by domain experts; (ii) development of a method for extending the traditional vector space, using domain ontologies; (iii) development of a method to support ontology learning, based on the discovery of new ontological relations expressed in non-structured information sources; (iv) development of a process to evaluate the semantic enrichment; (v) implementation of a proof-of-concept, named SENSE (Semantic Enrichment kNowledge SourcEs), which enables to validate the ideas established under the scope of this thesis; (vi) publication of several scientific articles and the support to 4 master dissertations carried out by the department of Electrical and Computer Engineering from FCT/UNL. It is worth mentioning that the work developed under the semantic referential covered by this thesis has reused relevant achievements within the scope of research European projects, in order to address approaches which are considered scientifically sound and coherent and avoid “reinventing the wheel”.European research projects - CoSpaces (IST-5-034245), CRESCENDO (FP7-234344) and MobiS (FP7-318452

A model for information retrieval driven by conceptual spaces

A retrieval model describes the transformation of a query into a set of documents. The question is: what drives this transformation? For semantic information retrieval type of models this transformation is driven by the content and structure of the semantic models. In this case, Knowledge Organization Systems (KOSs) are the semantic models that encode the meaning employed for monolingual and cross-language retrieval. The focus of this research is the relationship between these meanings’ representations and their role and potential in augmenting existing retrieval models effectiveness. The proposed approach is unique in explicitly interpreting a semantic reference as a pointer to a concept in the semantic model that activates all its linked neighboring concepts. It is in fact the formalization of the information retrieval model and the integration of knowledge resources from the Linguistic Linked Open Data cloud that is distinctive from other approaches. The preprocessing of the semantic model using Formal Concept Analysis enables the extraction of conceptual spaces (formal contexts)that are based on sub-graphs from the original structure of the semantic model. The types of conceptual spaces built in this case are limited by the KOSs structural relations relevant to retrieval: exact match, broader, narrower, and related. They capture the definitional and relational aspects of the concepts in the semantic model. Also, each formal context is assigned an operational role in the flow of processes of the retrieval system enabling a clear path towards the implementations of monolingual and cross-lingual systems. By following this model’s theoretical description in constructing a retrieval system, evaluation results have shown statistically significant results in both monolingual and bilingual settings when no methods for query expansion were used. The test suite was run on the Cross-Language Evaluation Forum Domain Specific 2004-2006 collection with additional extensions to match the specifics of this model

Construction project information management in a semantic web environment

Modem construction projects, characterised by severe fragmentation from both geographical and disciplinary perspectives, require accurate and timely sharing of information. Traditional information management systems operate on a textual basis and do not always consider the meaning of information. Current web-based information management technology supports information communication to a reasonable extent but still has many limitations, such as the lack of semanticawareness and poor interoperability of software applications. This research argues that Semantic Web technologies can enhance the efficiency of information management in construction projects by providing content-based and contextspecific information to project team members, and supporting the interoperation between independent applications. A Semantic Web-based Information Management System (Sams) for construction projects was created to demonstrate the above concept. The approach adopted for this research involved creating a new framework for Semantic Web-based information management. This extensible system framework enables the system to merge diverse construction information sources, ontologies and end-user applications into the overall Semantic Web environment. The semantic components developed in this research included a project document's annotation model, a project partner's user profile model, and several lightweight IFC-based ontologies for documented information management. This supports intelligent information management and interoperation between heterogeneous information sources and applications. The system framework, prototype annotations, and ontologies were applied to a concept demonstrator that illustrated how the project documents were annotated, accessed, converted, categorised, and retrieved on the basis of content and context. The demonstrator (named SwiMS) acts as a middleware, which mediates between user needs and the information sources. Information in project partners' documents were mapped and accessed intelligently. This involved the use of rule-based filtering and thus prevented the users from being overwhelmed by irrelevant documents or missing relevant ones in heterogeneous and distributed information sources. It also enabled the adaptation of documents to individual contexts and preferences, and the dynamic composition of various document management services. Evaluation of the system framework and demonstrator revealed that the system enhances the efficiency of construction information management, with the three most beneficial areas being project knowledge management, collaborative design and communication between project team members. The Swims annotations, ontologies and deductive rules are important technologies provide an innovative approach to managing construction information. These enable the information in construction documents, both structured documents and un-structured documents, to be interpretable by computers. This ensures the efficiency and precision of construction information management.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Denotative and Connotative Semantics in Hypermedia: Proposal for a Semiotic-Aware Architecture

In this article we claim that the linguistic-centered view within hypermedia systems needs refinement through a semiotic-based approach before real interoperation between media can be achieved. We discuss the problems of visual signification for images and video in dynamic systems, in which users can access visual material in a non-linear fashion. We describe how semiotics can help overcome such problems, by allowing descriptions of the material on both denotative and connotative levels. Finally we propose an architecture for a dynamic semiotic-aware hypermedia system

Denotative and connotative semantics in hypermedia: proposal for a semiotic-aware architecture

In this article we claim that the linguistic-centred view within hypermediasystems needs refinement through a semiotic-based approach before real interoperation between media can be achieved. We discuss the problems of visual signification for images and video in dynamic systems, in which users can access visual material in a non-linear fashion. We describe how semiotics can help overcome such problems, by allowing descriptions of the material on both denotative and connotative levels. Finally we propose an architecture for a dynamic semiotic-aware hypermedia system

concept paper

In this concept paper, we outline our working plan for the next phase of the Corporate Semantic Web project. The plan covers the period from March 2009 to March 2010. Corporate ontology engineering will improve the facilitation of agile ontology engineering to lessen the costs of ontology development and, especially, maintenance. Corporate semantic collaboration focuses the human- centered aspects of knowledge management in corporate contexts. Corporate semantic search is settled on the highest application level of the three research areas and at that point it is a representative for applications working on and with the appropriately represented and delivered background knowledge. Each of these pillars will yield innovative methods and tools during the project runtime until 2013. We propose a concept draft and a working plan covering the next twelve months for an integrative architecture of a Corporate Semantic Web provided by these three core pillars