Exploring the use of enterprise content management systems in different types of Organisations

Researchers and practitioners are starting to realize that it is unlikely that the full advantage of Electronic Content Management Systems (ECMS) can be realized unless both the technology capabilities and organisational context are taken into consideration. This study explores ECMS use in Replication, Diversification, Unification and Coordination type of organisations. A framework of ECMS-use is proposed suggesting different ways of using ECMS to support diverse organisational needs. Following a qualitative case study research approach, interviews were conducted with IT and business managers and ECMS users from each of the four types of organisations. Results suggest that, depending on the organisation’s business needs, ECMS use in organisations can be categorized as 1) Minimal-use, 2) Standard Adoption-use, 3) Customized-use or 4) Leveraged-use. Findings suggest that managers can gain more realistic benefits from ECMS use by understanding why and how different types of ECMS-use can support the way in which their businesses operate.

Supporting personalised content management in smart health information portals

Information portals are seen as an appropriate platform for personalised healthcare and wellbeing information provision. Efficient content management is a core capability of a successful smart health information portal (SHIP) and domain expertise is a vital input to content management when it comes to matching user profiles with the appropriate resources. The rate of generation of new health-related content far exceeds the numbers that can be manually examined by domain experts for relevance to a specific topic and audience. In this paper we investigate automated content discovery as a plausible solution to this shortcoming that capitalises on the existing database of expert-endorsed content as an implicit store of knowledge to guide such a solution. We propose a novel content discovery technique based on a text analytics approach that utilises an existing content repository to acquire new and relevant content. We also highlight the contribution of this technique towards realisation of smart content management for SHIPs.

An intelligent content discovery technique for health portal content management

Background: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics.Objective: This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new contentMethods: A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper.Results: The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management.Conclusions: The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current.

Identifying an appropriate content management system to develop clinical practice guidelines: a perspective

Clinical Practice Guidelines are widely used to inform and improve the quality and consistency of clinical practice. Developing and publishing Clinical Practice Guidelines is a complex task involving multiple components. Electronic Content Management Systems are increasingly employed to make this task more manageable. The Content Management System market offers a variety of options for publishing content on the Internet. However, there are limited products that comprehensively address the requirements of publishing Clinical Practice Guidelines. The authors are involved in publishing guidelines for remote clinical practitioners in Australia and present their perspective about identifying an appropriate Content Management System. Several elements essential to addressing their unique editing needs are defined in this article. Unfortunately, customisation is very expensive and laborious: few Content Management System providers can comprehensively meet the needs of Clinical Practice Guidelines publishing. Being pragmatic about the level of functionality a product can offer to support publication is essential.

High level segmentation of instructional videos based on content density

Automatically partitioning instructional videos into topic sections is a challenging problem in e-learning environments for efficient content management and cataloging. This paper addresses this problem by proposing a novel density function to delineate sections underscored by changes in topics in instructional and training videos. The content density function draws guidance from the observation that topic boundaries coincide with the ebb and flow of the 'density' of content shown in these videos. Based on this function, we propose two methods for high-level segmentation by determining topic boundaries. We study the performance of the two methods on eight training videos, and our experimental results demonstrate the effectiveness and robustness of the two proposed high-level segmentation algorithms for learning media.

On the extraction of thematic and dramatic functions of content in educational videos

In this paper, we propose novel computational models for the extraction of high level expressive constructs related to, namely thematic and dramatic functions of the content shown in educational and training videos. Drawing on the existing knowledge of film theory, and media production rules and conventions used by the filmmakers. we hypothesize key aesthetic elements contributing to convey these functions of the content. Computational models to extract them are then formulated and their performance evaluated on a set of ten educational and training videos is presented.

Using social software to support the teaching of IT professional practice

Social software has been used to support problem-based learning activities in a wholly online information technology (IT) professional practice course at Deakin University since 2006. When the course was first delivered, the authentic learning environment was a website, with an intranet and team forums created in Drupal, the open source content management system (CMS). Although this environment was suitable, feedback from students and teaching staff highlighted areas where improvements could be made. In the second year of the course, Joomla!, the open source CMS, in combination with Simple Machines Forum (SMF), the open source online discussion community software, was used to provide the website, as well as the intranet and team forums respectively. Feedback in 2007 was more positive, suggesting that the Joomla!-SMF social software combination and the features implemented, improved the learning and teaching experience in comparison to the 2006 version of the course.

A conceptual framework for the implementation of enterprise information portals in large organizations

Addressing the diversity in information requirements across the enterprise is a central challenge in enterprise content management. Enterprise information portals (EIPs) hold promise in this regard, offering each user a gateway to customized and personalized content. However, in large organizations EIP implementers face the complexity of tailoring portals for potentially thousands of users. A conceptual framework based on marketing fundamentals is developed to inform EIP implementation in this respect. It is argued that EIP implementers should view their user community as a number of distinct segments in order to address divergent needs more specifically (as opposed to a ‘one size fits all’ approach). For each identified segment, a ‘mix’ of content (product), distribution (place), promotion and price (cost) should be considered. The framework is applied to two cases of EIP implementation in large organizations. It is proposed that segmentation enables better planning of the overall EIP implementation effort. Considerations such as the number of user segments, customization, and personalization of content, and the funding of EIP development in large organizations are also discussed. The concepts elaborated here also hold theoretical relevance for other IS implementation contexts that involve very large usercommunities with diverse information

Blogs bother me : social media, journalism and the curriculum

This paper grew out of the authors’ interest in updating the journalism curriculum at AUT (Aukland University of Technology) to better reflect the impact of online media, including social media, on the work of journalists. The challenge for journalism educators is to remain relevant in rapidly changing news and education environments. Our study suggests that while the vast majority of students have some engagement with social media, particularly social networking, and are aware that it can be a powerful tool for journalists, they are still not entirely comfortable with its techniques and they are not experimenting with social media as a production platform as much as we first thought. In short, it appears that they do not have command of professional fluency with social media tools. In response to these findings we have begun to introduce some social media tools and processes directly into the units we teach, in particular: digital story-telling techniques; the use of Twitter and location-based applications; encouraging the ethical use of Facebook etc. for sourcing stories and talent for interviews; podcasting, soundslides and video for the Web, Dreamweaver, InDesign and PHP-based content management systems. We do not see the work to date as the end-point of the changes that we know are necessary, but we are acutely aware of the limitations (structural, institutional and financial) that suggest we should continue with this small-steps approach for the foreseeable future.

A probabilistic framework for extracting narrative act boundaries and semantics in motion pictures

This work constitutes the first attempt to extract the important narrative structure, the 3-Act storytelling paradigm in film. Widely prevalent in the domain of film, it forms the foundation and framework in which a film can be made to function as an effective tool for story telling, and its extraction is a vital step in automatic content management for film data. The identification of act boundaries allows for structuralizing film at a level far higher than existing segmentation frameworks, which include shot detection and scene identification, and provides a basis for inferences about the semantic content of dramatic events in film. A novel act boundary likelihood function for Act 1 and 2 is derived using a Bayesian formulation under guidance from film grammar, tested under many configurations and the results are reported for experiments involving 25 full-length movies. The result proves to be a useful tool in both the automatic and semi-interactive setting for semantic analysis of film, with potential application to analogues occuring in many other domains, including news, training video, sitcoms.

Finding the beat : an analysis of the rhythmic elements of motion pictures

This paper presents a new study on the application of the framework of Computational Media Aesthetics to the problem of automated understanding of film. Leveraging Film Grammar as the means to closing the "semantic gap" in media analysis, we examine film rhythm, a powerful narrative concept used to endow structure and form to the film compositionally and enhance its lyrical quality experientially. The novelty of this paper lies in the specification and investigation of the rhythmic elements that are present in two cinematic devices; namely motion and editing patterns, and their potential usefulness to automated content annotation and management systems. In our rhythm model, motion behavior is classified as being either nonexistent, fluid or staccato for a given shot. Shot neighborhoods in movies are then grouped by proportional makeup of these motion behavioral classes to yield seven high-level rhythmic arrangements that prove to be adept at indicating likely scene content (e.g. dialogue or chase sequence) in our experiments. The second part of our investigation presents a computational model to detect editing patterns as either metric, accelerated, decelerated or free. Details of the algorithm for the extraction of these classes are presented, along with experimental results on real movie data. We show with an investigation of combined rhythmic patterns that, while detailed content identification via rhythm types alone is not possible by virtue of the fact that film is not codified to this level in terms of rhythmic elements, analysis of the combined motion/editing rhythms can allow us to determine that the content has changed and hypothesize as to why this is so. We present three such categories of change and demonstrate their efficacy for capturing useful film elements (e.g. scene change precipitated by plot event), by providing data support from five motion pictures.

Scene extraction in motion pictures

This paper addresses the challenge of bridging the semantic gap between the rich meaning users desire when they query to locate and browse media and the shallowness of media descriptions that can be computed in today's content management systems. To facilitate high-level semantics-based content annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from fill production to determine when a scene change occurs. We then investigate different rules and conventions followed as part of Fill Grammar that would guide and shape an algorithmic solution for determining a scene. Two different techniques using intershot analysis are proposed as solutions in this paper. In addition, we present different refinement mechanisms, such as film-punctuation detection founded on Film Grammar, to further improve the results. These refinement techniques demonstrate significant improvements in overall performance. Furthermore, we analyze errors in the context of film-production techniques, which offer useful insights into the limitations of our method.