assessing learners' needs is an integral part of any curriculum and course design , namely english for specific purposes (esp), syllabus design, materials development, teaching methods and testing issues. critical approach to needs analysis, which is a relatively recent approach, acknowledges the rights of different stakeholders including teachers, students and administrators in the process of ...

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Much numerical information is visualized in graphs. However, this is a medium that is problematic for people with visual impairments. We have developed a system called iGraph which provides short verbal descriptions of the information usually depicted in graphs. This system was used as a preliminary solution that was validated through a process of User Needs Analysis (UNA). This process provide...

We consider the problem of query-focused multidocument summarization, where a summary containing the information most relevant to a user’s information need is produced from a set of topic-related documents. We propose a new method based on probabilistic latent semantic analysis, which allows us to represent sentences and queries as probability distributions over latent topics. Our approach comb...

Purpose – Citation and ranking information are becoming key aspects of knowledge management in academic and research institutions. By examining changing user needs and products, this paper aims to encourage information professionals to better understand and manage these resources and better respond to user needs. Design/methodology/approach – Literature reviews, work with faculty clients and in...

In this paper we present a general framework for type-based analyses of functional programs. Our framework is a generalisation of our earlier work on strictness analysis and was inspired by Burn's logical framework. The framework is parameterised by a set of types to represent properties and interpretations for constants in the language. To construct a new analysis, the user needs only to suppl...

Graph Data mining has ushered into new era with advanced data mining techniques. Mining Frequent Sub Graphs is the crucial area which appeals the ease of extracting the patterns in the graph. Typical graph data like Social Networks, Biological Networks (for metabolic pathways) and Computer Networks needs analysis of virtual networks of a category. Such graphs need be modeled as layered to disti...