A concept–relationship acquisition and inference approach for hierarchical taxonomy construction from tags

Author name used in this publication: W. M. WangAuthor name used in this publication: C. F. CheungAuthor name used in this publication: Adela S. M. Lau2009-2010 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Structuring the Quest for Strategic Alignment of Artificial Intelligence (AI): A Taxonomy of the Organizational Business Value of AI Use Cases

The deployment of Artificial Intelligence (AI) in businesses is said to provide significant benefits to organizations. However, many businesses struggle to align single AI use cases with the overall strategic business value contribution. Thus, we investigate the strategic characteristics that determine the business value contribution of AI use cases at an organizational level. We draw on academic literature and 106 AI use cases to develop a conceptually sound and empirically grounded taxonomy of the organizational business value of AI use cases. With the developed taxonomy, decision-makers are presented with a tool to systematically align AI use cases with strategic objectives. Moreover, our findings reveal how an AI use case can generate different business value contributions in different contexts, which provides researchers with a conceptual frame for informing their empirical research endeavors at the organizational level

Knowledge Discovery and Management within Service Centers

These days, most enterprise service centers deploy Knowledge Discovery and Management (KDM) systems to address the challenge of timely delivery of a resourceful service request resolution while efficiently utilizing the huge amount of data. These KDM systems facilitate prompt response to the critical service requests and if possible then try to prevent the service requests getting triggered in the first place. Nevertheless, in most cases, information required for a request resolution is dispersed and suppressed under the mountain of irrelevant information over the Internet in unstructured and heterogeneous formats. These heterogeneous data sources and formats complicate the access to reusable knowledge and increase the response time required to reach a resolution. Moreover, the state-of-the art methods neither support effective integration of domain knowledge with the KDM systems nor promote the assimilation of reusable knowledge or Intellectual Capital (IC). With the goal of providing an improved service request resolution within the shortest possible time, this research proposes an IC Management System. The proposed tool efficiently utilizes domain knowledge in the form of semantic web technology to extract the most valuable information from those raw unstructured data and uses that knowledge to formulate service resolution model as a combination of efficient data search, classification, clustering, and recommendation methods. Our proposed solution also handles the technology categorization of a service request which is very crucial in the request resolution process. The system has been extensively evaluated with several experiments and has been used in a real enterprise customer service center

"I just wanted a beautiful phone" - Checklist-based evaluation of smartphones usability for the elderly users

Mobile phone technology and user interface design have evolved into a multi-functional touchscreen-based smartphones with advanced capabilities and vast amount of applications. One potentially growing user group of the smartphones are elderly persons who have experienced the evolution of the technology during their adulthood. The objectives of this thesis were to chart what kind of requirements the persons over 65 years old have in relation to the mobile devices, and to evaluate how current user interface designs of smartphones fulfill the identified requirements. The evaluation process followed the existing framework designed for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors. The framework provides tools and a process to compare different designs. The process has four phases: plan, prepare, conduct evaluation and analyze results. In the planning phase Windows Phone 8.0 and Android 4.1 Jelly Bean were selected to represent different smartphone user interface designs. Items important from the elderly users’ viewpoint were identified during the preparation phase. Different heuristic checklists and design guidelines developed for mobile phones were also reviewed. Checklists used in the actual evaluation phase were composed by combining items essential to the elderly users and to the characteristics of the mobile phones. The evaluation was conducted by inspecting both Windows Phone and Android user interface designs against the checklists. The items of the checklists were analyzed and classified into five usability indicators: visual support of task goals, support of cognitive interaction, support of efficient interaction, functional support of user needs and ergonomic support. The classification allowed the comparison of the two designs in more generic level instead of comparing individual items in the checklists. Results of the checklist based expert evaluation indicated that the main differences were in the visual support of task goals and functional support of user needs. Overall simplicity, minimalistic design and fewer functions of Windows Phone reflect better the needs and desires of the elderly users

Optimising the information and knowledge environment within the Leicestershire Constabulary

Police forces in the UK have embarked on a recent Government initiative to implement mobile information technologies, which may be one of the most significant changes in policing history since the introduction of the two-way radio. The purpose of this research was to evaluate the impact of mobile technology on employees and existing information and knowledge intensive business processes within a UK police force, the Leicestershire Constabulary. [Continues.

Determinants of Success of the Open Source Selective Revealing Strategy: Solution Knowledge Emergence

Recent research suggests that firms may be able to create a competitive advantage by deliberately revealing specific problem knowledge beyond firm boundaries to open source meta-organisations such that new solution knowledge is created that benefits the focal firm more than its competitors (Alexy, George, & Salter, 2013). Yet, not all firms that use knowledge revealing strategies are successful in inducing the emergence of solution knowledge. The extant literature has as of yet not explained this heterogeneity in success of knowledge revealing strategies. Using a longitudinal database spanning the period from 1998 to end 2012 with more than 2 billion data points that was obtained from the Mozilla Foundation, one of the top open source meta-organisations, this dissertation identifies and measures the antecedent factors affecting successful solution knowledge emergence. The results reveal 35 antecedent factors that affect solution knowledge emergence in different ways across three levels of analysis. The numerous contributions to theory and practice that follow from the results are discussed