Intelligent classification of sketch strokes

This paper presents an intelligent method for classifying pen strokes in an on-line sketching system. The method, based on adaptive threshold and fuzzy knowledge with respect to curve's linearity and convexity, can identify sketch strokes (curves) into lines, circles, arcs, ellipses, elliptical arcs, loop lines, spring lines and free-form B-spline curves. The proposed method has proven to be fast, suitable for real-time classification and identification

Using Query Term Order for Result Summarisation

We report on two experiments performed to test the importance of Term Order in automatic summarisation. Experiment one was undertaken as part of DUC 2004 to which three systems were submitted, each with a different summarisation approach. The system that used document Term Order outperformed those that did not use Term Order in the ROUGE evaluation. Experiment two made use of human evaluations of search engine results, comparing our Query Term Order summaries with a simulation of current Google search engine result summaries in terms of summary quality. Our QTO system’s summaries aided users’ relevance judgements to a significantly greater extent than Google’s

Self-regulated learning in higher education : identifying key component processes

The concept of self-regulated learning is becoming increasingly relevant in the study of learning and academic achievement, especially in higher education, where quite distinctive demands are placed on students. Though several key theoretical perspectives have been advanced for self-regulated learning, there is consensus regarding the central role played by student perceptions of themselves as learners. There are two general aims of this positional article. The first is to emphasise self-regulated learning as a relevant and valuable concept in higher education. The second is to promote the study of those constituent elements considered most likely to develop our understanding beyond a mere description of those processes thought to be involved in self-regulated learning. A case is presented for learning style, academic control beliefs and student self-evaluation as key constructs which contribute to an increased understanding of student self-regulated learning and which facilitate the application of self-regulated learning in pedagogy by enhancing its tangibility and utility

Can Automatic Abstracting Improve on Current Extracting Techniques in Aiding Users to Judge the Relevance of Pages in Search Engine Results?

Current search engines use sentence extraction techniques to produce snippet result summaries, which users may find less than ideal for determining the relevance of pages. Unlike extracting, abstracting programs analyse the context of documents and rewrite them into informative summaries. Our project aims to produce abstracting summaries which are coherent and easy to read thereby lessening users’ time in judging the relevance of pages. However, automatic abstracting technique has its domain restriction. For solving this problem we propose to employ text classification techniques. We propose a new approach to initially classify whole web documents into sixteen top level ODP categories by using machine learning and a Bayesian classifier. We then manually create sixteen templates for each category. The summarisation techniques we use include a natural language processing techniques to weight words and analyse lexical chains to identify salient phrases and place them into relevant template slots to produce summaries

Evaluating Web Search Result Summaries

The aim of our research is to produce and assess short summaries to aid users’ relevance judgements, for example for a search engine result page. In this paper we present our new metric for measuring summary quality based on representativeness and judgeability, and compare the summary quality of our system to that of Google. We discuss the basis for constructing our evaluation methodology in contrast to previous relevant open evaluations, arguing that the elements which make up an evaluation methodology: the tasks, data and metrics, are interdependent and the way in which they are combined is critical to the effectiveness of the methodology. The paper discusses the relationship between these three factors as implemented in our own work, as well as in SUMMAC/MUC/DUC

Approaches to learning and competitive attitude in students in higher education

The degree to which individuals are able to nominate or change their approach to learning in order to meet the needs of the learning situation opens a lengthy and complex debate. Some evidence exists for a shift in approach depending on the experience of the learner and demands of the task, while other evidence is available which indicates stability of approach to learning over time and across task. The present study examines the relationship between approaches to learning and competitive attitude in undergraduate students. Previous research has reported a link between constructs such as achievement orientation and personality traits and cognitive strategies and it was suggested here that competitive attitude may be one mediating factor in students’ approaches to learning. Findings did not reveal a convincing relationship between competitiveness and approaches to learning and it is suggested that further exploration of trait constructs such as competitiveness may not yield meaningful evidence regarding the stability of students’ approaches to learning. There was also no evidence that the student experience of higher education cultivates competitiveness in students as cross-sectional comparisons of student year groups revealed only negligible and statistically non-significant differences in competitive attitude

Feature Selection for Summarising: The Sunderland DUC 2004 Experience

In this paper we describe our participation in task 1-very short single-document summaries in DUC 2004. The task chosen is related to our research project, which aims to produce abstracting summaries to improve search engine result summaries. DUC allowed us to produce summaries no longer than 75 characters, therefore we focused on feature selection to produce a set of key words as summaries instead of complete sentences. Three descriptions of our summarisers are given. Each of the summarisers performs very differently in the six ROUGE metrics. One of our summarisers which uses a simple algorithm to produce summaries without any supervised learning or complicated NLP technique performs surprisingly well among different ROUGE evaluations. Finally we give an analysis of ROUGE and participants’ results. ROUGE is an automatic evaluation of summaries package, which uses n-gram matching to calculate the overlapping between machine and human summaries, and indeed saves time for human evaluation. However, the different ROUGE metrics give different results and it is hard to judge which is the best for automatic summaries evaluation. Also it does not include complete sentences evaluation. Therefore we suggest some work needs to be done on ROUGE in the future to make it really effective

Progressive surface modeling scheme from unorganised curves

This paper presents a novel surface modelling scheme to construct a freeform surface progressively from unorganised curves representing the boundary and interior characteristic curves. The approach can construct a base surface model from four ordinary or composite boundary curves and support incremental surface updating from interior characteristic curves, some of which may not be on the final surface. The base surface is first constructed as a regular Coons surface and upon receiving an interior curve sketch, it is then updated. With this progressive modelling scheme, a final surface with multiple sub-surfaces can be obtained from a set of unorganised curves and transferred to commercial surface modelling software for detailed modification. The approach has been tested with examples based on 3D motion sketches; it is capable of dealing with unorganised design curves for surface modelling in conceptual design. Its limitations have been discussed

Incremental simulation modelling for Internet collaborative design

In order to support Web-based collaborative design in terms of transferring or updating models dynamically and efficiently, new incremental modelling and local updating strategies have been developed for simulation modelling application since simulation is more focused on visualisation effects than on geometry details. Based on an assembly connection concept, a drag-and-drop assembly method has also been proposed in simulation assembly. An assembly connection is defined as a group of assembly constraints and it makes assembly easier. A case study example is given to show the content of the proposed research

Development of the Web Users Self-Efficacy scale (WUSE)

The aim of this research was to develop a scale that could evaluate an individuals confidence in using the Internet. Web-based resources are becoming increasingly important within higher education and it is therefore vital that students and staff feel confident and competent in the access, provision, and utilisation of these resources. The scale developed here represents an extension of previous research (Cassidy & Eachus, 2002) that developed a measure of self-efficacy in the context of computer use. An iterative approach was used in the development of the Web User Self-Efficacy scale (WUSE) and the participants were recruited from the student body of a large University in the North West of the United Kingdom, and globally via a web site set up for this purpose. Initial findings suggest that the scale has acceptable standards of reliability and validity though work is continuing to refine the scale and improve the psychometric properties of the tool