Robust clustering of multi-type relational data via a heterogeneous manifold ensemble

High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

The role of relational capabilities in developing the capacity for supply chain innovation

The purpose of this paper is to gain a better understanding of the types of relational capabilities supply chain participants develop to enable ongoing supply chain innovation capacity building that produces improved business outcomes. This is exploratory research using qualitative data gathered by using five interviews, with the Australian road freight industry as the context. Two key relational capabilities and the improvement of four key business outcomes were identified as being present in the interaction of freight transport service providers with members of their supply chain. The data also demonstrates that by entering into competence building relationships with customers and suppliers firms can build capabilities that will increase their capacity for supply chain innovation. Even in short term arm’s length relationships firms can acquire improved skills behaviours and practices that enhance their operation effectiveness and the efficiency of the supply chain relationships.

What’s in a handshake? Exploring business-to-business relational exchange

Despite its importance in the development of competitive advantage, attempts to unify diverse classifications of business-to-business relational exchange have been largely unsuccessful. We used 18 semi-structured, in-depth interviews with managers from a wide range of industries to explain the business-to-business relational exchange construct. Analysis of the data revealed that business-to-business relational exchange comprises five key dimensions. These are communication, compatibility, commitment, trust and power symmetry. The research highlights the importance of personal interaction in business relationships and provided additional insights into the importance of affective commitment. In addition we reveal a number of negative consequences of affective commitment, which have been previously unexplored. A new conceptual model of business-to-business relational exchange is presented, which synthesises these findings and directs future research.

Generative systems as relational bridges

Generative media systems present an opportunity for users to leverage computational systems to make sense of complex media forms through interactive and collaborative experiences. Generative music and art are a relatively new phenomenon that use procedural invention as a creative technique to produce music and visual media. These kinds of systems present a range of affordances that can facilitate new kinds of relationships with music and media performance and production. Early systems have demonstrated the potential to provide access to collaborative ensemble experiences to users with little formal musical or artistic expertise. This paper examines the relational affordances of these systems evidenced by selected field data drawn from the Network Jamming Project. These generative performance systems enable access to unique ensemble with very little musical knowledge or skill and they further offer the possibility of unique interactive relationships with artists and musical knowledge through collaborative performance. In this presentation I will focus on demonstrating how these simulated experiences might lead to understandings that may be of educational and social benefit. Conference participants will be invited to jam in real time using virtual interfaces and to view video artifacts that demonstrate an interactive relationship with artists.

Relational factors that explain supply chain relationships

Purpose: The purpose of this paper is to gain a better understanding of the types of relationships that exist along the supply chain and the capabilities that are needed to manage them effectively. ---------- Design/methodology/approach: This is exploratory research as there has been little empirical research into this area. Quantitative data were gathered by using a self-administered questionnaire, using the Australian road freight industry as the context. There were 132 usable responses. Inferential and descriptive analysis, including factor analysis, confirmatory factor and regression analysis was used to examine the predictive power of relational factors in inter-firm relationships. ---------- Findings: Three factors were identified as having significant influence on relationships: sharing, power and interdependency. “Sharing” is the willingness of the organisation to share resources with other members of the supply chain. “Power” relates to exercising control based on experience, knowledge and position in the supply chain. “Interdependency” is the relative levels of dependency along the supply chain. ---------- Research limitations/implications: The research only looks at the Australian road freight industry; a wider sample including other industries would help to strengthen the generalisability of the findings. ---------- Practical implications: When these factors are correlated to the types of relationship, arm's length, cooperation, collaboration and alliances, managerial implications can be identified. The more road freight businesses place importance on power, the less they will cooperate. The greater the importance of sharing and interdependency, the greater is the likelihood of arm's length relationships. ---------- Originality/value: This paper makes a contribution by describing empirical work conducted in an under-researched but important area – supply chain relationships in the Australian road freight industry.

On governing collaborative Information Technology (IT) : a relational perspective

Organizations today invest in collaborative IT to engage in collaborative alliances to sustain or improve their competitive positions. Effective use of this collaborative IT in an alliance requires a deeper understanding of their governance structures. This effort is to ensure the sustainability of these alliances. Through the relational view of the firm, we suggest relational lateral IT-steering committees, relational IT operational committees, and relational IT performance management systems as IT governance structures for collaborative alliances. We then incorporate these structures, develop a model for approaches to governing collaborative IT, and evaluate the effectiveness for such governance structures in the IT-dependent alliances. We suggest that IT governance efforts of an alliance should contribute to their collaborative rent. We also suggest that the collaborative rent of an alliance would relate to the business value of its alliance partners. Field survey data containing 192 responses indicates a positive influence of the suggested IT governance efforts of the alliance on the collaborative rent of the alliance. The results also suggest a positive impact of the collaborative rent of the alliance on the business value of the alliance partners.

Data transformations in custom digital workflows : property graphs as a data model for user-defined mappings

This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.

Empirical Support For an Item and Relational Conceptualization of Sponsorship

This paper outlines how commercial sponsorship can be conceptualized using an item and relational information framework, and supports this with empirical data. The model presented allows for predictions about consumer memory for sponsorship information, and hence has both theoretical and practical value. Data are reported which show that sponsors considered congruent with an event benefit by providing consumers with sponsor-specific item information, while sponsors considered incongruent benefit by providing sponsor-event relational information. Overall the provision of sponsor-event relational information is shown to result in superior memory to the provision of sponsor-specific item information, which is superior to basic sponsor mentions.

Empirical support for an item and relational conceptualization of sponsorship

This paper outlines how commercial sponsorship can be conceptualized using an item and relational information framework, and supports this with empirical data. The model presented allows for predictions about consumer memory for sponsorship information, and hence has both theoretical and practical value. Data are reported which show that sponsors considered congruent with an event benefit by providing consumers with sponsor-specific item information, while sponsors considered incongruent benefit by providing sponsor-event relational information. Overall the provision of sponsor-event relational information is shown to result in superior memory to the provision of sponsor-specific item information, which is superior to basic sponsor mentions.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Reversible and semi-blind relational database watermarking

Database watermarking has received significant research attention in the current decade. Although, almost all watermarking models have been either irreversible (the original relation cannot be restored from the watermarked relation) and/or non-blind (requiring original relation to detect the watermark in watermarked relation). This model has several disadvantages over reversible and blind watermarking (requiring only watermarked relation and secret key from which the watermark is detected and original relation is restored) including inability to identify rightful owner in case of successful secondary watermarking, inability to revert the relation to original data set (required in high precision industries) and requirement to store unmarked relation at a secure secondary storage. To overcome these problems, we propose a watermarking scheme that is reversible as well as blind. We utilize difference expansion on integers to achieve reversibility. The major advantages provided by our scheme are reversibility to high quality original data set, rightful owner identification, resistance against secondary watermarking attacks, and no need to store original database at a secure secondary storage.

Managing knowledge for asset management : shifting from process to relational frames

The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.