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Case adaptation continues to be one of the more difficult aspects of case-based reasoning to automate. This paper looks at several techniques for utilising the implicit knowledge contained in a case base for case adaptation in case-based reasoning systems. The most significant of the techniques proposed are a moderately successful data mining technique and a highly successful artificial neural network technique. Their effectiveness was evaluated on a footwear design problem.

Software design process has been followed and widely used to describe logical organisation of software using different types of models. However, when it comes to remote communication over software design, it is prone to miscommunication, misunderstanding or misinterpretation especially with ambiguous terms or people having different backgrounds and knowledge of the software design process. This motivates the use of unified knowledge representation of software design process i.e. software design process ontology for communications and coordination. The knowledge representation introduced here in the form of software design process ontology is based on a formal description of the software design process using the web ontology language OWL. Software design process knowledge is defined or captured in a formal and machine processable fashion. The software design process knowledge is then open and facilitates the sharing of software design among software engineers. We discuss software design process ontology development in this paper.

Resolving heterogeneity among various protein data sources is a crucial problem if we want to gain more information about proteomics process. Information from multiple protein databases like PDB, SCOP, and UniProt need to integrated to answer user queries. Issues of Semantic Heterogeneity haven?t been addressed so far in Protein Informatics. This paper outlines protein data source composition approach based on our existing work of Protein Ontology (PO). The proposed approach enables semi-automatic interoperation among heterogeneous protein data sources. The establishment of semantic interoperation over conceptual framework of PO enables us to get a better insight on how information can be integrated systematically and how queries can be composed. The semantic interoperation between protein data sources is based on semantic relationships between concepts of PO. No other such generalized semantic protein data interoperation framework has been considered so far.

Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need to be vigilant in monitoring the state of competitiveness of their platforms. In the technology post-adoption period, healthcare organizations use multiple data sources to search for technology-related information to maintain technology parity with, or dominance over their competitors. Firstly this study seeks to answer the following research question: what approaches do healthcare organizations employ with regard to managing diverse sources of data and information in order to sustain their technology competitiveness. Then as an initial step in this direction, in this paper we discuss the conceptual foundation for the phenomenon of data and information sources management capability for the proteomics domain. This is done by discussing the case of Protein Data Source Integration by Protein Ontology.

Several approaches for data interoperation identified by Karp have been implemented for biological databases. We extend Karp's approach for interoperation not only to protein databases but also to knowledge bases and other information sources. This paper outlines algebra for protein data source composition based on our existing work of Protein Ontology (PO). In this paper we consider the case of establishing correspondence between various protein data sources using semantic relationships over the conceptual framework of PO. Here we provide specific set of relationships over PO framework to cover data semantics for integrating data information from diverse protein data sources. These relationships help in defining semantic query algebra for PO to efficiently reason and query the instance store.

The CACHERPframework leverages the relative object popularity as the sole parameter for dynamic cache size tuning. In the process it consistently maintains the prescribed cache hit ratio on the fly by deriving the popularity ratio from the current statistics. As a result the accuracy of the statistical CACHERPoperation is independent of changes in the Internet traffic pattern that may switch suddenly. The contribution by the novel CACHERPframework is that by adaptively maintaining the given hit ratio it effectively reduces the end-to-end information retrieval roundtrip time (RTT) and frees more bandwidth for sharing. This bandwidth would otherwise be consumed in transferring large amounts of data from remote data sources to the proxy server before it is given to the client or requestor.

Online advertising is aimed to promote and sell products and services of various companies in the global market through internet. In 2005, it was estimated that companies spent $10B in web advertisements, and it is expected to grow by 25-30% in the next few years. The advertisements can be displayed in the search results as sponsored links, on the web sites, etc. Further, these advertisements are personalized based on demographic targeting or on information gained directly from the user. In a standard setting, an advertiser provides the publisher with its advertisements and they agree on some commission for each customer action. This agreement is done in the presence of Internet Advertising commissioners, who represent the middle person between Internet Publishers and Internet Advertisers. The publisher, motivated by the commission paid by the advertisers, displays the advertisers’ links in its search results. Since each player in this scenario can earn huge revenue through this procedure, there is incentive to falsely manipulate the procedure by extracting forbidden information of the customer action. By passing this forbidden information to the other party, one can generate extra revenue. This paper discusses an algorithm for detecting such frauds in web advertising networks.

Ontologies are the foundation of the Semantic Web (SW) and one of the keys necessary to its success. Conversely, ontology views hold the promise of; (a) provide a manageable portion of a larger ontology for the localized applications and users, (b) enable precise extraction of sub-onlogies of a larger ontology that commits to the main ontology, (c) enable localized customization and usage of the portion of a larger ontology and (d) enable interoperability between large ontology bases and applications. Therefore, it is interesting to look at ontology views and their desired properties, as there exists no agreed upon standard, methodology or formalism to specify, define and materialize ontology views. Thus, in this paper, we elaborate on our own research direction towards proposing a meaningful ontology view formalism and its associated semantics.

Object-Oriented (OO) conceptual modelling offers the power in describing and modelling real-word data semantics and their inter-relationships in a form that is precise and comprehensible to users [1]. Conversely, XML [2] is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems and databases. With the increased reliance on such self-describing, schema-based, semi-structured data language/(s), there exists a requirement to model, design, and manipulate XML data and the associated semantics at a higher level of abstraction than at the instance level.However, existing Object-Oriented conceptual modelling languages provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints, while most semi-structured schema languages lack the ability to provide higher levels of abstraction (such as conceptual models) that are easily understood by humans. To this end, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we use XML view as a case in point and proposed to model engineering. In this paper, we use XML views as a case in point and propose to model dynamic properties of a layered XML view model [3] using eXtensible Semantic (XSemantic) nets.In data molding, we can group the existing view models into four categories, namely [3]; (a) classical (or relational) views, (b) Object-Oriented (OO) views, (c) semi-structured (namely XML) view models [4-6, 3] and (d) view models for Semantic Web. Here, we focus only on view models for XML

Software development is a knowledge intensive process and the information generated in open source software development projects is typically housed in a central Internet repository. Open source repositories typically contains vast amounts of information, much of it unstructured, meaning that even if a question has previously been discussed and dealt with it is not a trivial task to locate it. This can lead to rework and confusion amongst developers and possibly deter new developers from getting involved in the project in the first place. This paper will present the case for an open source software development ontology. Such an ontology would enable better categorization of information and the development of sophisticated knowledge portals in order to better organize community knowledge and increase efficiency in the open source development process.

EXtensible Markup Language (XML) has rapidly gained importance as a mechanism for the exchange of information amongst heterogeneous sources over the web. In order to deal with the challenging task of managing the large volumes of data appearing, encoded in XML transactional databases, the need to explore the XML Document Warehouse (XDW) approach is initiated. The applications of the Requirement Engineering (RE) process and Object-Oriented conceptual models have proven their usefulness in building successful software models and solutions. In this paper we introduce an integration methodology for the development of XDWs. Initially we provide a formal notation of the structural design for the XDW conceptual model. Secondly we focus on deriving requirements for the XDWs by exploring the Goal-Question Metric (GQM) approach. We adapt and extend this concept to XDWs and introduce a method for developing warehouse requirements considering user viewpoints and organizational objectives. The implementation of our proposed warehouse requirement derivation model is demonstrated using a case study example extracted from a simplified real-world scenario.

Tree mining has recently attracted a lot of interest in areas such as Bioinformatics, XML mining, Web mining, etc. We are mainly concerned with mining frequent induced and embedded subtrees. While more interesting patterns can be obtained when mining embedded subtrees, unfortunately mining such embedding relationships can be very costly. In this paper, we propose an efficient approach to tackle the complexity of mining embedded subtrees by utilizing a novel Embedding List representation, Tree Model Guided enumeration, and introducing the Level of Embedding constraint. Thus, when it is too costly to mine all frequent embedded subtrees, one can decrease the level of embedding constraint gradually up to 1, from which all the obtained frequent subtrees are induced subtrees. Our experiments with both synthetic and real datasets against two known algorithms for mining induced and embedded subtrees, FREQT and TreeMiner, demonstrate the effectiveness and the efficiency of the technique.

Presently, organizations make significant investments in biomedical data and information sources. These investments are expected to produce reduction of errors and quality improvements in data management and analysis. To sustain achievements in quality and efficiency, healthcare organizations need to be vigilant in monitoring the state of competitiveness of their platforms. In the technology post-adoption period, healthcare organizations use multiple data sources to search for technology-related information to maintain technology parity with, or dominance over their competitors. Firstly this study seeks to answer the following research question: what approaches do healthcare organizations employ with regard to managing diverse sources of data and information in order to sustain their technology competitiveness. Then as an initial step in this direction, in this paper we discuss the conceptual foundation for the phenomenon of data and information sources management capability for the proteomics domain. This is done by discussing the case of Protein Data Source Integration by Protein Ontology.

Electronic commerce has pushed and benefited from the development of intelligent mobile agents technology. One of the reasons is electronic commerce needs remote searching and negotiating between one customer and a number of E-shops. This chapter presents a new secure electronic commerce protocol. We provide the security mechanisms through using a new proxy signature scheme implied in the protocol. The digital age has enabled widespread access to and collection of data. While there are several advantages to ubiquitous access to data, there is also the potential for breaching the privacy of individuals. Therefore, preserving privacy is maintained for both the customer and the e-shops in the proposed e-transactions. In addition, fair privacy is one of the characteristics of the new protocol. The proposed e-transactions use intelligent mobile agents to help customers make buying decisions, as well as providing post-purchase service for customers, and providing post-purchase auditing for e-shops. Therefore, it will improve the successful e-commerce to satisfy customers and increase sales of e-shops.

The growing development of web-based reputation systems in the 21st century will have a powerful social and economic impact on both business entities and individual customers, because it makes transparent quality assessment on products and services to achieve customer assurance in the distributed web-based Reputation Systems. The web-based reputation systems will be the foundation for web intelligence in the future. Trust and Reputation help capture business intelligence through establishing customer trust relationships, learning consumer behaviour, capturing market reaction on products and services, disseminating customer feedback, buyers' opinions and end-user recommendations. It also reveals dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviours, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behaviour, sales, reputation of sellers, providers, products and services. Given the importance of reputation in this paper, we propose ontology for reputation. In the business world we can consider the reputation of a product or the reputation of a service or the reputation of an agent. In this paper we propose ontology for these entities that can help us unravel the components and conceptualise the components of reputation of each of the entities.

Advances in technology and the growth of life sciences are generating ever increasing amounts of data. High-throughput techniques are regularly used to capture thousands of data points in an experiment. The results of these experiments normally end up in scientific databases and publications. Although there have been concerted efforts to capture more scientific data in specialist databases, it is generally acknowledged that only 20 per cent of biological knowledge and data is available in a structured format. The remaining 80 per cent of biological information is hidden in the unstructured scientific results and texts. Protein Ontology (PO) discussed in this paper provides a common structured vocabulary for this structured and unstructured information and provides researchers a medium to share knowledge in proteomics domain. It consists of concepts, which are data descriptors for proteomics data and the relations among these concepts. Protein Ontology provides description for protein domains that can be used to describe proteins in any organism.

Moving towards automated service selection, contract negotiation, and contract fulfilment remains a promising vision for E-commerce systems. Trust is one of the main reasons why this vision is not put into practice in current E-commerce systems. Various theoretical models and technical concepts are in place to facilitate crucial factors such as system interoperability or communication-level security. However, proven models, to measure social values such as trustworthiness, reputation or credibility of service consumers and service providers in loosely coupled, distributed E-commerce systems, are the missing factors which prevent the adoption of automated service interaction. This paper demonstrates the application of our Fuzzy trust model in an Ecommerce platform. We apply an exemplary business scenario to demonstrate the usage of our Fuzzy trust model.

In automated and unsupervised multi-agent environments, where agents act on behalf of their stakeholders, the measurement and computation of trust is a key building block upon which all business interaction scenarios rely. In environments, where the individual and independent calculation of trustworthiness values for future negotiation partners is desired, flexible algorithms and models imitating human reasoning are crucial. This paper introduces a trust evaluation model that imitates human reasoning by using fuzzy logic concepts. Furthermore, post-interaction processes such as business interaction reviews and credibility adjustment are used to continuously build and refine an information repository for future trust evaluation processes. Fuzzy logic offers a mathematical approach encompassing uncertainty and tolerance of imprecise data, and combined with our highly customizable model, it allows to meet the security needs of different stakeholders.

Along with sensor networks popularly utilized in the practical applications, to design optimistic security mechanisms is becoming a big challenge within the wireless sensor networks. As a result, it is imperative to propose a taxonomy of attacks on wireless sensor networks, since good security mechanism should address the attacks on wireless sensor networks. This paper presents the first work of the taxonomy of attacks on wireless sensor networks in a systematic way. This will help researchers in the area of wireless sensor networks to better understand wireless sensor network security and design more optimistic security countermeasures for wireless sensor networks.

In this paper, we propose an approach to integrate protein information from various data sources by defining a Protein Ontology. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow description and analysis of relationships between various proteins. Protein Ontology uses relevant protein data sources of information like PDB, SCOP, and OMIM. Protein Ontology describes: Protein Sequence and Structure Information, Protein Folding Process, Cellular Functions of Proteins, Molecular Bindings internal and external to Proteins, and Constraints affecting the Final Protein Conformation. Details about Protein Ontology are available online at http://www.proteinontology.info/.

In this paper, we proposed a Protein Ontology to integrate protein data and information from various Protein Data Sources. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow description and analysis of relationships between various proteins. Protein Ontology uses relevant protein data sources of information like PDB, SCOP, and OMIM. Protein Ontology describes: Protein Sequence and Structure Information, Protein Folding Process, Cellular Functions of Proteins, Molecular Bindings internal and external to Proteins, and Constraints affecting the Final Protein Conformation. We also created a database of 10 Major Prion Proteins available in various Protein data sources, based on the vocabulary provided by Protein Ontology. Details about Protein Ontology are available online athttp://www.proteinontology.info/.

Since the early software models, abstraction and conceptual semantics have proven their importance in software engineering methodologies. For example, Object-Oriented conceptual modelling offers the power in describing and modelling real-world data semantics and their inter-relationships in a form that is precise and comprehensible to users. Conversely, XML is becoming the dominant standard for storing, describing and interchanging data among various Enterprises Information Systems and databases. With the increased reliance on such self-describing, schema-based, semi-structured data language/(s), there exists a requirement to model, design, and manipulate XML data and associated semantics at a higher level of abstraction than at the instance level. But, existing Object-Oriented conceptual modelling languages provide insufficient modelling constructs for utilizing XML schema like data descriptions and constraints, and most semi-structured schema languages lack the ability to provide higher levels of abstraction (such as conceptual models) that are easily understood by humans. To this end, it is interesting to investigate conceptual and schema formalisms as a means of providing higher level semantics in the context of XML-related data engineering. In this paper, we use XML view as a case in point and present a three-layered view model with illustrated examples taken from a real-world application domain. We focus on conceptual and schema view definitions, view constraints, and the conceptual query operators.

The growing development of web-based reputation systems in the 21st century will have a powerful social and economic impact on both business entities and individual customers, because it makes transparent quality assessment on products and services to achieve customer assurance in the distributed web-based Reputation Systems. The web-based reputation systems will be the foundation for web intelligence in the future. Trust and Reputation help capture business intelligence through establishing customer trust relationships, learning consumer behaviour, capturing market reaction on products and services, disseminating customer feedback, buyers? opinions and end-user recommendations. It also reveals dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviours, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behaviour, sales, reputation of sellers, providers, products and services. Given the importance of reputation in this paper, we propose ontology for reputation. In the business world we can consider the reputation of a product or the reputation of a service or the reputation of an agent. In this paper we propose ontology for these entities that can help us unravel the components and conceptualize the components of reputation of each of the entities.

Trust is one of the most fuzzy, dynamic and complex concepts in both social and business relationships. The difficulty in measuring Trust and predicting Trustworthiness in service-oriented network environments leads to many questions. These include issues such as how to measure the willingness and capability of individuals in the Trust dynamic and how to assign a concrete level of Trust to an individual or Agent. In this paper, we analyze the fuzzy, dynamic and complex nature of Trust.The dynamic nature of Trust creates the biggest challenge in measuring Trust and predicting Trustworthiness. In order to develop a Trustworthiness Measure and Prediction Method, we first need to understand what we can actually measure in a Trust Relationship.

XML is becoming increasingly a popular medium in industrial informatics for (a) storing and representing unstructured and semi-structured information such as web content and (b) messaging between heterogeneous data sources. For both these purposes it is important to provide a high level, model driven solution to design and implement websites that are capable of handling heterogonous schemas and documents. For this, we need a methodology, that provides higher level of abstraction of the domain in question (here the web) with rigorously defined standards that are to be more widely understood by all stakeholders of the system. To achieve this, in this paper, we propose an XMLview driven design and architecture solution (methodology) for web engineering called xWeb. This methodology uses Object-Oriented (OO) conceptual modelling techniques in combination with proven higher-level web user interface engineering and data engineering techniques that provides a comprehensive, yet generic web design methodology. Also, xWeb architecture utilizes XML technologies without requirements for a middleware and provides support for web portals.

As small to medium sized logistics companies strive to be more competitive with the larger ones, computer processes will progressively be carried out differently than in the traditional manner. Progressively more and more computation will occur on the Internet rather than just make use of it as a gateway. Programs will be distributed throughout a network and the World Wide Web and work together in a highly developed manner. A virtual logistics network provides an organisational framework for collaboration in this manner is proposed. In this paper we propose a virtual logistics network that provides an organizational framework for collaboration between small to middle sized companies. This employs an e-hub structure utilizing XML based mobile agents to provide seamless integration between isolated information systems for small to medium sized logistic providers.