Ahmad Kayed

Bio: Ahmad Kayed is an academic researcher from Middle East University. The author has contributed to research in topics: Ontology (information science) & Ontology-based data integration. The author has an hindex of 12, co-authored 34 publications receiving 309 citations. Previous affiliations of Ahmad Kayed include Applied Science Private University & Monash University.

Extracting ontological concepts for tendering conceptual structures

Abstract: 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.

Towards an Ontology for Software Product Quality Attributes

Abstract: Recently, Quality Assurance concept has been developed increasingly to be included in many of our life existing fields; financial, industrial, trading, computing, etc. Software Quality Product Attributes (SWQAs) have been created as a matter of applying the QA concept on the results of web or desktop application development process, to fit the products with the organizational and global market standards and goals, and to provide it with a competitive advantage value. Web application or software product quality is composed of many attributes such as portability, usability, reliability, modularity. During the recent years, many researchers discussed and presented software attributes in their works which showed that till now there is a lack of consensus on the semantic of many of concepts and terminologies used in this field. Our work is focusing on studying Software Product Quality Attributes concepts and terminologies. We conduct several experiments to extract the main concepts for SWQAs. The results show that there is a number of concepts that are frequently used to describe these attributes. Summarizing and formalizing the semantic of the attributes into these concepts presents a common understanding and agreement on the semantic of SWQPAs which can be used by software engineers, researchers, practitioners, and stakeholders.

Processing Over Encrypted Data: Between Theory and Practice

Abstract: Data encryption is a common approach to protect the confidentiality of users' data. However, when computation is required, the data must be decrypted before processing. The decryption-for-processing approach causes critical threats. For instance, a compromised server may lead to the leakage of data or cryptographic keys. On the other hand, data owners are concerned since the data is beyond their control. Thus, they look for mechanisms to achieve strong data protection. Accordingly, alternatives for protecting data become essential. Consequently, the trend of processing over encrypted data starts to arise along with a rapidly growing literature. This paper surveys applications, tools, building blocks, and approaches that can be used to directly process encrypted data (i.e., without decrypting it). The purpose of this survey is to provide an overview of existing systems and approaches that can be used to process encrypted data, discuss commercial usage of such systems, and to analyze the current developments in this area

A framework to Deal with Missing Data in Data Sets

Abstract: Most information systems usually have some missing values due to unavailable data Missing values minimizing the quality of classification rules generated by a data mining system Missing vales also affecting the quantity of classification rules achieved by the data mining system Missing values could influence the coverage percentage and number of reducts generated Missing values lead to the difficulty of extracting useful information from that data set Solving the problem of missing data is of a high priority in the field of data mining and knowledge discovery Replacing missing values by a specific value should not affect the quality of the data Four different models for dealing with missing data were studied A framework is established that remove inconsistencies before and after filling the attributes of missing values with the new expected value as generated by one of the four models Comparative results were discussed and recommendations were concluded

Ontology learning from text: A look back and into the future

Abstract: Ontologies are often viewed as the answer to the need for interoperable semantics in modern information systems. The explosion of textual information on the Read/Write Web coupled with the increasing demand for ontologies to power the Semantic Web have made (semi-)automatic ontology learning from text a very promising research area. This together with the advanced state in related areas, such as natural language processing, have fueled research into ontology learning over the past decade. This survey looks at how far we have come since the turn of the millennium and discusses the remaining challenges that will define the research directions in this area in the near future.

Applications of ontologies in requirements engineering: a systematic review of the literature

Abstract: There is an increase use of ontology-driven approaches to support requirements engineering (RE) activities, such as elicitation, analysis, specification, validation and management of requirements. However, the RE community still lacks a comprehensive understanding of how ontologies are used in RE process. Thus, the main objective of this work is to investigate and better understand how ontologies support RE as well as identify to what extent they have been applied to this field. In order to meet our goal, we conducted a systematic literature review (SLR) to identify the primary studies on the use of ontologies in RE, following a predefined review protocol. We then identified the main RE phases addressed, the requirements modelling styles that have been used in conjunction with ontologies, the types of requirements that have been supported by the use of ontologies and the ontology languages that have been adopted. We also examined the types of contributions reported and looked for evidences of the benefits of ontology-driven RE. In summary, the main findings of this work are: (1) there are empirical evidences of the benefits of using ontologies in RE activities both in industry and academy, specially for reducing ambiguity, inconsistency and incompleteness of requirements; (2) the majority of studies only partially address the RE process; (3) there is a great diversity of RE modelling styles supported by ontologies; (4) most studies addressed only functional requirements; (5) several studies describe the use/development of tools to support different types of ontology-driven RE approaches; (6) about half of the studies followed W3C recommendations on ontology-related languages; and (7) a great variety of RE ontologies were identified; nevertheless, none of them has been broadly adopted by the community. Finally, we conclude this work by showing several promising research opportunities that are quite important and interesting but underexplored in current research and practice.

Achieving Business Process Model Interoperability Using Metamodels and Ontologies.

Abstract: Common userand business-requirements demand an integrated view on the multitude of available information resources that are processed in a variety of heterogeneous information systems. Therefore, the research field of semantic integration which is a prerequisite for the interoperability of systems is of high importance. In this paper we focus on the semantic interoperability of business process models which is, for instance, of relevance for the interoperability of standard software or workflow engines that are configured by such processes. In order to perform such a task, the use of two alternative concepts is often proposed in literature: metamodels and ontologies. These two concepts are most often used without really reflecting their characteristics and their relationship to one another which is a critical shortcoming. Therefore, we provide an extensive discussion of these concepts which establishes the basis for their combined use for achieving semantic interoperability of business processes. In this context we will also discuss basic approaches for the mapping of model elements and ontology constructs which is of importance for providing inherent semantics. The paper is concluded with an outlook on the ongoing implementation of the proposed interoperability approach and its possible benefits for the area of service oriented architectures.