Supporting knowledge strategy in consulting organizations : codification, personalization or both

This paper reports on results from an ongoing study of the information infrastructure support for organizational knowledge strategy. We assess the applicability and predictions of the widely cited model of Hansen, Nohria and Tierney’s on knowledge strategy and infrastructure support. We do so by means of two case studies that we conducted in the consulting sector. Our findings indicate support for the Hansen et al.’s model as each of the organizations has predominately pursued a knowledge strategy consistent with the model’s predictions. However, we also find that in so doing, organizations can incur significant opportunity costs if either a codification or a personalization knowledge strategy is allowed to predominate to such an extent that it crowds-out the alternative knowledge strategy.

Finding line of action of the force exerted on erect spine based on lateral bending test in personalization of scoliotic spine models

In multi-body models of scoliotic spine, personalization of mechanical properties of joints significantly improves reconstruction of the spine shape. In personalization methods based on lateral bending test, simulation of bending positions is an essential step. To simulate, a force is exerted on the spine model in the erect position. The line of action of the force affects the moment of the force about the joints and thus, if not correctly identified, causes over/underestimation of mechanical properties. Therefore, we aimed to identify the line of action, which has got little attention in previous studies. An in-depth analysis was performed on the scoliotic spine movement from the erect to four spine positions in the frontal plane by using pre-operative X-rays of 18 adolescent idiopathic scoliosis (AIS) patients. To study the movement, the spine curvature was considered as a 2D chain of micro-scale motion segments (MMSs) comprising rigid links and 1-degree-of-freedom (DOF) rotary joints. It was found that two MMSs representing the inflection points of the erect spine had almost no rotation (0.0028° ± 0.0021°) in the movement. The small rotation can be justified by weak moment of the force about these MMSs due to very small moment arm. Therefore, in the frontal plane, the line of action of the force to simulate the left/right bending position was defined as the line that passes through these MMSs in the left/right bending position. Through personalization of a 3D spine model for our patients, we demonstrated that our line of action could result in good estimates of the spine shape in the bending positions and other positions not included in the personalization, supporting our proposed line of action.

Enhancing web-based adaptive learning with colored timed petri net

One of the issues for Web-based learning applications is to adaptively provide personalized instructions for different learning activities. This paper proposes a high level colored timed Petri Net based approach to providing some level of adaptation for different users and learning activities. Examples are given to demonstrate how to realize adaptive interfaces and personalization. Future directions are also discussed at the end of this paper.

Mobile location based services

Mobility has become a key factor around the world, as the use of ubiquitous devices, including laptops, personal digital assistants (PDAs), and mobile phones, are increasingly becoming part of daily life (Steinfield, 2004). Adding mobility to computing power, and with advanced personalization of technologies, new business applications are emerging in the area of mobile communications (Jagoe, 2003). The fastest growing segment among these applications is location-based services. This article offers a brief overview of services and their supporting technologies, and provides an outlook for their future.

Formulating an organizational knowledge strategy : the influence of existing IT infrastructure

This paper questions the influence of a pre-existing information technology (IT) infrastructure on the formulation of an organizational knowledge strategy. We draw on a classification of four different strategic views of IT infrastructure and explore how the historic investment in IT infrastructure enables and constrains the formulation of knowledge strategy in four case organizations. The four case organizations are representative of different scenarios of historic investments in IT infrastructure and knowledge strategy formulation. Our findings indicate that an IT infrastructure that is minimal or fragmented constrains the formulation of an explicit knowledge strategy. We further find that an extensive existing IT infrastructure enables the pursuit of an explicit knowledge strategy, but that even an elaborate IT infrastructure can introduce some constraints on IT facilitated knowledge processes in the organization.

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

Six sigma approach to improve quality in E-services : an empirical study in Jordan

In the last two decades, Six Sigma approach has found its success in manufacturing sectors. The relevance of Six Sigma methodologies in service sector has been realised more recently. This paper investigates the application of Six Sigma approach to improve quality in electronic services (e-services) as more and more countries are adopting e-services as a means of providing services to their community and people through the Web. In particular, this paper presents a case study about the use of Six Sigma model to measure the customer satisfaction and quality levels achieved in e-services that were recently launched by public sector organisations in a developing country, such as Jordan. An empirical study consisting of 280 participating customers of Jordan‘s e-services is conducted and the problems are identified through the DMAIC phases of Six Sigma. The service quality levels are measured and analysed using six main criteria, namely, Website Design, Reliability, Responsiveness, Personalization, Information Quality, and System Quality. The overall result of the study indicating a 74% customer satisfaction with a Six Sigma level of 2.12 has enabled the Greater Amman Municipality to identify the usability issues associated with their e-services offered by public sector organisations and to take the leads from the results of the study to improve customer satisfaction. The aim of the paper is not only to implement Six Sigma as a measurement-based strategy for improving e-customer service quality in a newly launched e-service programme, but also to help widen its scope in investigating other service dimensions and perform comparative studies in other developing countries as future research.

"You Tube and I Find" - personalizing multimedia content access

Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhereVfrom personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, fromcreation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itselfVits affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today’s facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user’s personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems.

Privacy preserving for tagging recommender systems

Tagging recommender systems allow Internet users to annotate resources with personalized tags. The connection among users, resources and these annotations, often called afolksonomy, permits users the freedom to explore tags, and to obtain recommendations. Releasing these tagging datasets accelerates both commercial and research work on recommender systems. However, adversaries may re-identify a user and her/his sensitivity information from the tagging dataset using a little background information. Recently, several private techniques have been proposed to address the problem, but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes an private releasing algorithm to perturb users' profile in a strict privacy notion, differential privacy, with the goal of preserving a user's identity in a tagging dataset. The algorithm includes three privacy preserving operations: Private Tag Clustering is used to shrink the randomized domain and Private Tag Selection is then applied to find the most suitable replacement tags for the original tags. To hide the numbers of tags, the third operation, Weight Perturbation, finally adds Lap lace noise to the weight of tags We present extensive experimental results on two real world datasets, Delicious and Bibsonomy. While the personalization algorithmis successful in both cases.

Participatory sensing and education: helping the community mitigate sleep disturbance from traffic noise

Purpose – This paper aims to present a project in Australia, where participants use smartphones to measure the level of traffic noise in their homes. Through the data collected, participants learn if they are subjected to sleep disturbances and, if so, understand how they can manage the issue to protect their health. The project also has a secondary purpose: the local council would like to engage its community through the exercise and be seen as acting on the community’s problems.

Community aged care case managers transitioning to consumer directed care: more than procedural change required

Consumer directed care (CDC) is increasing in community aged care. However, limited information is available to successfully transition social workers and other case managers to their new role. This paper reports on a case study of six senior case managers who supervised staff in three Australian community-aged care agencies as they transitioned from agency directed care to consumer directed care. A change management framework was used to analyse the qualitative data collected in 12 semistructured interviews. A key finding is that changes in values, attitudes, and organisational culture are needed before staff can fully implement CDC principles of service user self-determination, empowerment, and choice. Process changes needed to assist staff transition to CDC are: using a change management strategy that maximises certainty; monitoring and responding to feelings of anxiety through ongoing consultations; and providing ongoing education and support in group sessions.

Privacy preserving data release for tagging recommender systems

Tagging recommender systems allow Internet users to annotate resources with personalized tags. The connection among users, resources and these annotations, often called a folksonomy, permits users the freedom to explore tags, and to obtain recommendations. Releasing these tagging datasets accelerates both commercial and research work on recommender systems. However, tagging recommender systems has been confronted with serious privacy concerns because adversaries may re-identify a user and her/his sensitive information from the tagging dataset using a little background information. Recently, several private techniques have been proposed to address the problem, but most of them lack a strict privacy notion, and can hardly resist the number of possible attacks. This paper proposes an private releasing algorithm to perturb users' profile in a strict privacy notion, differential privacy, with the goal of preserving a user's identity in a tagging dataset. The algorithm includes three privacy-preserving operations: Private Tag Clustering is used to shrink the randomized domain and Private Tag Selection is then applied to find the most suitable replacement tags for the original tags. To hide the numbers of tags, the third operation, Weight Perturbation, finally adds Laplace noise to the weight of tags. We present extensive experimental results on two real world datasets, De.licio.us and Bibsonomy. While the personalization algorithm is successful in both cases, our results further suggest the private releasing algorithm can successfully retain the utility of the datasets while preserving users' identity.

Modelling personal preferences for Top-N movie recommendations

Modelling the temporal dynamics of personal preferences is still under-developed despite the rapid development of personalization. In this paper, we observe that the user preference styles tend to change regularly following certain patterns in the context of movie recommendation systems. Therefore, we propose a Preference Pattern model to capture the user preference styles and their temporal dynamics, and apply this model to improve the accuracy of the Top-N movie recommendations. Precisely, a preference pattern is defined as a set of user preference styles sorted in a time order. The basic idea is to model user preference styles and their temporal dynamics by constructing a representative subspace with an Expectation-Maximization (EM)-like algorithm, which works in an iterative fashion by refining the global and the personal preference styles simultaneously. Then, the degree which the recommendations match the active user's preference styles, can be estimated by measuring its reconstruction error from its projection on the representative subspace. The experiment results indicate that the proposed model is robust to the data sparsity problem, and can significantly outperform the state-of-the-art algorithms on the Top-N movie recommendations in terms of accuracy.

Pavement cafes as the activity zone in the social life of neighbourhood centres

This paper reports the findings from a research project that examines the relationship between urban design and the physical environment, and aspects of social and communal life in suburbs. Australian suburbs are perceived to be lacking in vitality and sociability. To address this, three suburban commercial streets were selected for investigation. Through documents and maps of the residents’ activities and behaviour, this study aims to identify the popular zones of activity and investigate the physical characteristics that encourage a sociable atmosphere in activity zones. The observation of activities in the three streets has been registered in tables relative to the date and time of occurrence. According to the behavioural mappings, the zones of activity are mostly shaped around pavement cafes and popular everyday food stores. Since more than half the activities have been observed to be initiated from the pavement cafes, this paper will investigate how the physical qualities of commercial streets such as the width of the pavements, personalization, soft edges and greenery have contributed to the pavement café culture in the selected neighbourhood centres.

Supporting adaptive tour with high level petri nets

One of the issues for tour planning applications is to adaptively provide personalized advices for different types of tourists and tour activities. This paper proposes a high level Petri Nets based approach to providing some level of adaptation by implementing adaptive navigation in a tour node space. The new model supports dynamic reordering or removal of tour nodes along a tour path; it supports multiple travel modes and incorporates multimodality within its tour planning logic to derive adaptive tour. Examples are given to demonstrate how to realize adaptive interfaces and personalization. Future directions are also discussed at the end of this paper.