Structuring visual exploratory analysis of skill demand

The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employed by skilled practitioners in defining career pathways, to identify where, when and how to update their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science, where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on

The application of user log for online business environment using content-based Image retrieval system

Over the past few years, inter-query learning has gained much attention in the research and development of content-based image retrieval (CBIR) systems. This is largely due to the capability of inter-query approach to enable learning from the retrieval patterns of previous query sessions. However, much of the research works in this field have been focusing on analyzing image retrieval patterns stored in the database. This is not suitable for a dynamic environment such as the World Wide Web (WWW) where images are constantly added or removed. A better alternative is to use an image's visual features to capture the knowledge gained from the previous query sessions. Based on the previous work (Chung et al., 2006), the aim of this paper is to propose a framework of inter-query learning for the WWW-CBIR systems. Such framework can be extremely useful for those online companies whose core business involves providing multimedia content-based services and products to their customers

Using multimedia to enhance the accessibility of the learning environment for disabled students: reflections from the Skills for Access project

As educators' awareness of their responsibilities towards ensuring the accessibility of the learning environment to disabled students increases, significant debate surrounds the implications of accessibility requirements on educational multimedia. There would appear to be widespread concern that the fundamental principles of creating accessible web‐based materials seem at odds with the creative and innovative use of multimedia to support learning and teaching, as well as concerns over the time and cost of providing accessibility features that can hold back resource development and application. Yet, effective use of multimedia offers a way of enhancing the accessibility of the learning environment for many groups of disabled students. Using the development of ‘Skills for Access’, a web resource supporting the dual aims of creating optimally accessible multimedia for learning, as an example, the attitudinal, practical and technical challenges facing the effective use of multimedia as an accessibility aid in a learning environment will be explored. Reasons why a holistic approach to accessibility may be the most effective in ensuring that multimedia reaches its full potential in enabling and supporting students in learning, regardless of any disability they may have, will be outlined and discussed

Unsupervised Visual and Textual Information Fusion in Multimedia Retrieval - A Graph-based Point of View

Multimedia collections are more than ever growing in size and diversity. Effective multimedia retrieval systems are thus critical to access these datasets from the end-user perspective and in a scalable way. We are interested in repositories of image/text multimedia objects and we study multimodal information fusion techniques in the context of content based multimedia information retrieval. We focus on graph based methods which have proven to provide state-of-the-art performances. We particularly examine two of such methods : cross-media similarities and random walk based scores. From a theoretical viewpoint, we propose a unifying graph based framework which encompasses the two aforementioned approaches. Our proposal allows us to highlight the core features one should consider when using a graph based technique for the combination of visual and textual information. We compare cross-media and random walk based results using three different real-world datasets. From a practical standpoint, our extended empirical analysis allow us to provide insights and guidelines about the use of graph based methods for multimodal information fusion in content based multimedia information retrieval.Comment: An extended version of the paper: Visual and Textual Information Fusion in Multimedia Retrieval using Semantic Filtering and Graph based Methods, by J. Ah-Pine, G. Csurka and S. Clinchant, submitted to ACM Transactions on Information System

A framework for accessible m-government implementation

The great popularity and rapid diffusion of mobile technologies at worldwide level has also been recognised by the public sector, leading to the creation of m-government. A major challenge for m-government is accessibility – the provision of an equal service to all citizens irrespective of their psychical, mental or technical capabilities. This paper sketches the profiles of six citizen groups: Visually Impaired, Hearing Impaired, Motor Impaired, Speech Impaired, Cognitive Impaired and Elderly. M-government examples that target the aforementioned groups are discussed and a framework for accessible m-government implementation with reference to the W3C Mobile Web Best Practices is proposed

Surveying Persons with Disabilities: A Source Guide (Version 1)

As a collaborator with the Cornell Rehabilitation Research and Training Center on Disability Demographics and Statistics, Mathematica Policy Research, Inc. has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data. In an effort to provide the public with an up-to-date and easily accessible source of research on the methodological issues associated with surveying persons with disabilities, MPR has prepared a Source Guide of material related to this topic. The Source Guide contains 150 abstracts, summaries, and references, followed by a Subject Index, which cross references the sources from the Reference List under various subjects. The Source Guide is viewed as a “living document,” and will be periodically updated