The doctoral research abstract. Vol:9 2016 / Institute of Graduate Studies, UiTM

FOREWORD: Seventy three doctoral graduands will be receiving their scroll today signifying their achievements in completing their PhD journey. The novelty of their research is shared with you through The Doctoral Abstracts on this auspicious occasion, UiTM 84th Convocation. We are indeed proud that another 73 scholarly contributions to the world of knowledge and innovation have taken place through their doctoral research ranging from Science and Technology, Business and Administration, and Social Science and Humanities. As we rejoice and celebrate your achievement, we would like to acknowledge dearly departed Dr Halimi Zakaria’s scholarly contribution entitled “Impact of Antecedent Factors on Collaborative Technologies Usage among Academic Researchers in Malaysian Research Universities”. He has left behind his discovery to be used by other researchers in their quest of pursuing research in the same area, a discovery that his family can be proud of. Graduands, earning your PhD is not the end of discovering new ideas, invention or innovation but rather the start of discovering something new. Enjoy every moment of its discovery and embrace that life is full of mystery and treasure that is waiting for you to unfold. As you unfold life’s mystery, remember you have a friend to count on, and that friend is UiTM. Congratulations for completing this academic journey. Keep UiTM close to your heart and be our ambassador wherever you go. / Prof Emeritus Dato’ Dr Hassan Said Vice Chancellor Universiti Teknologi MAR

Ontological Engineering: What are Ontologies and How Can We Build Them?

Ontologies are formal, explicit specifications of shared conceptualizations. There is much literature on what they are, how they can be engineered and where they can be used inside applications. All these literature can be grouped under the term “Ontological Engineering,” which is defined as the set of activities that concern the ontology development process, the ontology lifecycle, the principles, methods and methodologies for building ontologies, and the tool suites and languages that support them. In this chapter we provide an overview of Ontological Engineering, describing the current trends, issues and problem

Artificial intelligence as law:Presidential address to the seventeenth international conference on artificial intelligence and law

Information technology is so ubiquitous and AI's progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be good for us. But how to establish proper safeguards for AI? One strong answer readily available is: consider the problems and solutions studied in AI & Law. AI & Law has worked on the design of social, explainable, responsible AI aligned with human values for decades already, AI & Law addresses the hardest problems across the breadth of AI (in reasoning, knowledge, learning and language), and AI & Law inspires new solutions (argumentation, schemes and norms, rules and cases, interpretation). It is argued that the study of AI as Law supports the development of an AI that is good for us, making AI & Law more relevant than ever

An ontological representation of a taxonomy for cybercrime

The modern phenomenon of cybercrime raises issues and challenges on a scale that has few precedents. A particular central concern is that of establishing clarity about the conceptualization of cybercrime and its growing economic cost to society. A further related concern is focused on developing appropriate legal and policy responses in a context where crime transcends national jurisdictions and physical boundaries. Both are predicated on a better understanding of cybercrime. Efforts at defining and classifying cybercrime by the use of taxonomies to date have largely been descriptive with resulting ambiguities. This paper contributes a semi-formal approach to the development of a taxonomy for cybercrime and offers the conceptual language and accompanying constraints with which to describe cybercrime examples. The approach uses the ontology development platform, Protégé and the Unified Modeling Language (UML) to present an initial taxonomy for cybercrime that goes beyond the descriptive accounts previously offered. The taxonomy is illustrated with examples of cybercrimes both documented in the Protégé toolset and also using UML

An explainable data-driven approach to web directory taxonomy mapping

5noThe spread of e-commerce and web applications has fostered the integration of cross-domain business activities. To efficiently retrieve products and services, web directories allow customers to browse multiple-level taxonomies to find specific products or services according to a predefined categorization. Providers need to periodically update web directory lists by aligning in-house taxonomies to domain-specific hierarchies coming from external sources. However, such taxonomy mapping procedures are often semi-automatic and rely on traditional word disambiguation techniques to capture the semantics behind categories and products descriptions. Hence, the flexibility and explainability of the underlying models are quite limited. This paper proposes an automated, explainable approach to web directory taxonomy mapping based on text categorization. It exploits two complementary word-based text representations: a frequency-based representation, which captures syntactic text similarities, and an embedding one, which highlights the underlying semantic relationships among words. Since the proposed solution is purely data-driven, it can be successfully applied to business domains where there is a lack of semantic models. The frequency-based text representation has shown to be particularly suitable for driving the automated taxonomy mapping procedure, whereas the embedding space has been profitably used to provide local explanations of the category assignments.partially_openopenElena Daraio, Luca Cagliero, Silvia Anna Chiusano, Paolo Garza, Giuseppe RicuperoDaraio, Elena; Cagliero, Luca; Chiusano, SILVIA ANNA; Garza, Paolo; Ricupero, Giusepp