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.

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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.