A framework for supporting knowledge representation – an ontological based approach

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de ComputadoresThe World Wide Web has had a tremendous impact on society and business in just a few years by making information instantly available. During this transition from physical to electronic means for information transport, the content and encoding of information has remained natural language and is only identified by its URL. Today, this is perhaps the most significant obstacle to streamlining business processes via the web. In order that processes may execute without human intervention, knowledge sources, such as documents, must become more machine understandable and must contain other information besides their main contents and URLs. The Semantic Web is a vision of a future web of machine-understandable data. On a machine understandable web, it will be possible for programs to easily determine what knowledge sources are about. This work introduces a conceptual framework and its implementation to support the classification and discovery of knowledge sources, supported by the above vision, where such sources’ information is structured and represented through a mathematical vector that semantically pinpoints the relevance of those knowledge sources within the domain of interest of each user. The presented work also addresses the enrichment of such knowledge representations, using the statistical relevance of keywords based on the classical vector space model concept, and extending it with ontological support, by using concepts and semantic relations, contained in a domain-specific ontology, to enrich knowledge sources’ semantic vectors. Semantic vectors are compared against each other, in order to obtain the similarity between them, and better support end users with knowledge source retrieval capabilities

Collaborative semantic web browsing with Magpie

Web browsing is often a collaborative activity. Users involved in a joint information gathering exercise will wish to share knowledge about the web pages visited and the contents found. Magpie is a suite of tools supporting the interpretation of web pages and semantically enriched web browsing. By automatically associating an ontology-based semantic layer to web resources, Magpie allows relevant services to be invoked as well as remotely triggered within a standard web browser. In this paper we describe how Magpie trigger services can provide semantic support to collaborative browsing activities

Dynamic Assembly for System Adaptability, Dependability, and Assurance

(DASASA) ProjectAuthor-contributed print ite

WAQS : a web-based approximate query system

The Web is often viewed as a gigantic database holding vast stores of information and provides ubiquitous accessibility to end-users. Since its inception, the Internet has experienced explosive growth both in the number of users and the amount of content available on it. However, searching for information on the Web has become increasingly difficult. Although query languages have long been part of database management systems, the standard query language being the Structural Query Language is not suitable for the Web content retrieval. In this dissertation, a new technique for document retrieval on the Web is presented. This technique is designed to allow a detailed retrieval and hence reduce the amount of matches returned by typical search engines. The main objective of this technique is to allow the query to be based on not just keywords but also the location of the keywords within the logical structure of a document. In addition, the technique also provides approximate search capabilities based on the notion of Distance and Variable Length Don\u27t Cares. The proposed techniques have been implemented in a system, called Web-Based Approximate Query System, which contains an SQL-like query language called Web-Based Approximate Query Language. Web-Based Approximate Query Language has also been integrated with EnviroDaemon, an environmental domain specific search engine. It provides EnviroDaemon with more detailed searching capabilities than just keyword-based search. Implementation details, technical results and future work are presented in this dissertation

IDL-XML based information sharing model for enterprise integration

CJM is a mechanized approach to problem solving in an enterprise. Its basis is intercommunication between information systems, in order to provide faster and more effective decision making process. These results help minimize human error, improve overall productivity and guarantee customer satisfaction. Most enterprises or corporations started implementing integration by adopting automated solutions in a particular process, department, or area, in isolation from the rest of the physical or intelligent process resulting in the incapability for systems and equipment to share information with each other and with other computer systems. The goal in a manufacturing environment is to have a set of systems that will interact seamlessly with each other within a heterogeneous object framework overcoming the many barriers (language, platforms, and even physical location) that do not grant information sharing. This study identifies the data needs of several information systems of a corporation and proposes a conceptual model to improve the information sharing process and thus Computer Integrated Manufacturing. The architecture proposed in this work provides a methodology for data storage, data retrieval, and data processing in order to provide integration at the enterprise level. There are four layers of interaction in the proposed IXA architecture. The name TXA (DDL - XML Architecture for Enterprise Integration) is derived from the standards and technologies used to define the layers and corresponding functions of each layer. The first layer addresses the systems and applications responsible for data manipulation. The second layer provides the interface definitions to facilitate the interaction between the applications on the first layer. The third layer is where data would be structured using XML to be stored and the fourth layer is a central repository and its database management system

A Smart Products Lifecycle Management (sPLM) Framework - Modeling for Conceptualization, Interoperability, and Modularity

Autonomy and intelligence have been built into many of today’s mechatronic products, taking advantage of low-cost sensors and advanced data analytics technologies. Design of product intelligence (enabled by analytics capabilities) is no longer a trivial or additional option for the product development. The objective of this research is aimed at addressing the challenges raised by the new data-driven design paradigm for smart products development, in which the product itself and the smartness require to be carefully co-constructed. A smart product can be seen as specific compositions and configurations of its physical components to form the body, its analytics models to implement the intelligence, evolving along its lifecycle stages. Based on this view, the contribution of this research is to expand the “Product Lifecycle Management (PLM)” concept traditionally for physical products to data-based products. As a result, a Smart Products Lifecycle Management (sPLM) framework is conceptualized based on a high-dimensional Smart Product Hypercube (sPH) representation and decomposition. First, the sPLM addresses the interoperability issues by developing a Smart Component data model to uniformly represent and compose physical component models created by engineers and analytics models created by data scientists. Second, the sPLM implements an NPD3 process model that incorporates formal data analytics process into the new product development (NPD) process model, in order to support the transdisciplinary information flows and team interactions between engineers and data scientists. Third, the sPLM addresses the issues related to product definition, modular design, product configuration, and lifecycle management of analytics models, by adapting the theoretical frameworks and methods for traditional product design and development. An sPLM proof-of-concept platform had been implemented for validation of the concepts and methodologies developed throughout the research work. The sPLM platform provides a shared data repository to manage the product-, process-, and configuration-related knowledge for smart products development. It also provides a collaborative environment to facilitate transdisciplinary collaboration between product engineers and data scientists

Automatic message annotation and semantic interface for context aware mobile computing

This thesis was submitted for the degree of Docter of Philosophy and awarded by Brunel University.In this thesis, the concept of mobile messaging awareness has been investigated by designing and implementing a framework which is able to annotate the short text messages with context ontology for semantic reasoning inference and classification purposes. The annotated metadata of text message keywords are identified and annotated with concepts, entities and knowledge that drawn from ontology without the need of learning process and the proposed framework supports semantic reasoning based messages awareness for categorization purposes. The first stage of the research is developing the framework of facilitating mobile communication with short text annotated messages (SAMS), which facilitates annotating short text message with part of speech tags augmented with an internal and external metadata. In the SAMS framework the annotation process is carried out automatically at the time of composing a message. The obtained metadata is collected from the device’s file system and the message header information which is then accumulated with the message’s tagged keywords to form an XML file, simultaneously. The significance of annotation process is to assist the proposed framework during the search and retrieval processes to identify the tagged keywords and The Semantic Web Technologies are utilised to improve the reasoning mechanism. Later, the proposed framework is further improved “Contextual Ontology based Short Text Messages reasoning (SOIM)”. SOIM further enhances the search capabilities of SAMS by adopting short text message annotation and semantic reasoning capabilities with domain ontology as Domain ontology is modeled into set of ontological knowledge modules that capture features of contextual entities and features of particular event or situation. Fundamentally, the framework SOIM relies on the hierarchical semantic distance to compute an approximated match degree of new set of relevant keywords to their corresponding abstract class in the domain ontology. Adopting contextual ontology leverages the framework performance to enhance the text comprehension and message categorization. Fuzzy Sets and Rough Sets theory have been integrated with SOIM to improve the inference capabilities and system efficiency. Since SOIM is based on the degree of similarity to choose the matched pattern to the message, the issue of choosing the best-retrieved pattern has arisen during the stage of decision-making. Fuzzy reasoning classifier based rules that adopt the Fuzzy Set theory for decision making have been applied on top of SOIM framework in order to increase the accuracy of the classification process with clearer decision. The issue of uncertainty in the system has been addressed by utilising the Rough Sets theory, in which the irrelevant and indecisive properties which affect the framework efficiency negatively have been ignored during the matching process.The Ministry of Higher Education and Scientific Research (IRAQ

EPOS : evolving personal to organizational knowledge spaces

EPOS will leverage the user´s personal workspace with its manyfold native information structures to his personal knowledge space and in cooperation with other personal workspaces contribute to the organizational knowledge space which is represented in the organizational memory. This first milestone presents results from the project´s first year in the areas of the personal informational model, user observation for context elicitation, collaborative information retrieval and information visualization

Content warehouses

Nowadays, content management systems are an established technology. Based on the experiences from several application scenarios we discuss the points of contact between content management systems and other disciplines of information systems engineering like data warehouses, data mining, and data integration. We derive a system architecture called "content warehouse" that integrates these technologies and defines a more general and more sophisticated view on content management. As an example, a system for the collection, maintenance, and evaluation of biological content like survey data or multimedia resources is shown as a case study