Idea mining is a new and interesting field in the areas of information retrieval research. The thoughts of people are helpful to improve strategic decision making. This paper demonstrates the efficient computational methods of idea characterization based concept by extracting the interesting hidden data from unstructured texts which come in many forms and sizes. It may be stored in patents, publications, reports, documents, Internet etc. We briefly discussed a number of successful text mining tools and text classification to extract the idea with a combination of idea mining measures.
The digital divide between developed and developing countries is increasing rapidly. However, a number of developing countries are striving to narrow this gap by enriching their societies through the introduction of ICT based business activities. Knowledge management and E-learning are examples of such ICT supported activities. Knowledge management applications are aimed to provide organizations with tools to manage their business knowledge, while the focus of e-learning has always been on managing the delivery of academic knowledge. Efforts to integrate both areas of research are lacking. This paper presents a knowledge management approach for e-learning applications. It highlights the joint characteristics of the two concepts and proposes a KM view of e-learning. The aim is to streamline the transfer of educational content among the stakeholders of a typical e-learning environment. The proposed approach has been implemented in the Kingdom of Saudi Arabia which is a developing country where many cultural issues have to be taken into consideration.
Abstracts of research papers are meant to provide a brief condensed overview of respective research topics. This includes a glimpse of the new idea that the paper proposes. The aim of the research presented here is to investigate the feasibility of the effect of text position in the idea identification. The abstracts are structured in the form of introduction, body, and conclusion. It is hypothesized that research ideas tend to be phrased in conclusion section of paper abstracts. 25 abstracts of the scientific papers were used to automatically identify the position of ideas within abstract sections. The results support the notion that the conclusion of the abstracts significantly represents the ideas.
Curbing the global environmental threats become a worldwide issue. Over the years, significant scientific evidences emerged that highlighted the relationship between massive industrialization and global environmental threats. For this reason, all types of industrialization are undergoing radical re-engineering; the aim is to manufacture goods and services that are efficient, safer and environmental-friendly. In terms of software industry, sustainable software engineering has become a hot research topic; it spans sustainability issues in all stages of software life cycle. This paper proposes a design rationale model for humancomputer interaction design. The proposed model is an adaptation of the QOC deliberation model, where green computing guidelines are used as criteria for the evaluation of interface design decisions. As part of the collaborative decision making process pertaining interactions design decisions, we believe that there is a need to provide designers with contextual guidance that help to construct a shared mental model about the design problem, and how it is influenced by the recommendations of the Green IT campaign. For this reason, we incorporated the Green computing guidelines within the elements of the proposed design rationale model. The paper is also presenting a prototypical implementation of the proposed model.
Abstract:The human behavior has always been very influential in systems engineering. In fact, AI methods and techniques are largely influenced by the human behavior in the form of mental and mechanical capabilities. The human learning, persevering and then recalling knowledge is the focal point in artificial intelligence research. But less attention is paid to forgetting as one of the characteristics that have a very positive role in human intelligence. This paper seeks to integrate data forgetting as part of the behavior of case-based reasoning systems. The aim is to improve the performance of CBR systems by filtering out irrelevant cases as part of the machine behavior in the form of CBR systems. The paper presents a prototypical implementation of the of a forgettable CBR system that provides course recommendations as part of student registration system. Experimental work has been carried out using historical data of postgraduate students in the Computer science department, Tripoli University, Libya.
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