Profiling Attitudes for Personalized Information Provision

PAROS is a generic system under design whose goal is to offer personalization, recommendation, and other adaptation services to information providing systems. In its heart lies a rich user model able to capture several diverse aspects of user behavior, interests, preferences, and other attitudes. The user model is instantiated with profiles of users, which are obtained by analyzing and appropriately interpreting potentially arbitrary pieces of user-relevant information coming from diverse sources. These profiles are maintained by the system, updated incrementally as additional data on users becomes available, and used by a variety of information systems to adapt the functionality to the users’ characteristics

PRIMA — Privacy research through the perspective of a multidisciplinary mash up

Based on a summary description of privacy protection research within three fields of inquiry, viz. social sciences, legal science, and computer and systems sciences, we discuss multidisciplinary approaches with regard to the difficulties and the risks that they entail as well as their possible advantages. The latter include the identification of relevant perspectives of privacy, increased expressiveness in the formulation of research goals, opportunities for improved research methods, and a boost in the utility of invested research efforts

Methodological considerations concerning manual annotation of musical audio in function of algorithm development

In research on musical audio-mining, annotated music databases are needed which allow the development of computational tools that extract from the musical audiostream the kind of high-level content that users can deal with in Music Information Retrieval (MIR) contexts. The notion of musical content, and therefore the notion of annotation, is ill-defined, however, both in the syntactic and semantic sense. As a consequence, annotation has been approached from a variety of perspectives (but mainly linguistic-symbolic oriented), and a general methodology is lacking. This paper is a step towards the definition of a general framework for manual annotation of musical audio in function of a computational approach to musical audio-mining that is based on algorithms that learn from annotated data. 1

Big Data in Critical Infrastructures Security Monitoring: Challenges and Opportunities

Critical Infrastructures (CIs), such as smart power grids, transport systems, and financial infrastructures, are more and more vulnerable to cyber threats, due to the adoption of commodity computing facilities. Despite the use of several monitoring tools, recent attacks have proven that current defensive mechanisms for CIs are not effective enough against most advanced threats. In this paper we explore the idea of a framework leveraging multiple data sources to improve protection capabilities of CIs. Challenges and opportunities are discussed along three main research directions: i) use of distinct and heterogeneous data sources, ii) monitoring with adaptive granularity, and iii) attack modeling and runtime combination of multiple data analysis techniques.Comment: EDCC-2014, BIG4CIP-201

Developing a Structurational Approach to Electronic Customer Relationship Management (ECRM)

The literature on culture provides a set of general concepts and ideas as a way of looking at the world (Hofstede 1980). However, the typologies of culture have inherent weaknesses, e.g., they do not reflect the variety of values and attitude that may exist in a country, nor do they explain how cultures have developed over time (Skok and Doringer 2001). These limitations lead our research to investigate the potential impact of cultural differences on eCRM using concepts from Structuration Theory by ,. In this paper the authors highlight the dimensions of culture and its potential impact on eCRM systems, using a Structurational analysis based on . The authors use the practice lens for studying technology in organizations based on , to develop a framework of studying different agencies and their structures within eCRM systems context. The authors conclude by a framework of Structurational analysis of eCRM systems displaying different agencies and their structures. This framework of analysis will be used to conduct a comparative case study in future research

Data and Predictive Analytics Use for Logistics and Supply Chain Management

Purpose The purpose of this paper is to explore the social process of Big Data and predictive analytics (BDPA) use for logistics and supply chain management (LSCM), focusing on interactions among technology, human behavior and organizational context that occur at the technology’s post-adoption phases in retail supply chain (RSC) organizations. Design/methodology/approach The authors follow a grounded theory approach for theory building based on interviews with senior managers of 15 organizations positioned across multiple echelons in the RSC. Findings Findings reveal how user involvement shapes BDPA to fit organizational structures and how changes made to the technology retroactively affect its design and institutional properties. Findings also reveal previously unreported aspects of BDPA use for LSCM. These include the presence of temporal and spatial discontinuities in the technology use across RSC organizations. Practical implications This study unveils that it is impossible to design a BDPA technology ready for immediate use. The emergent process framework shows that institutional and social factors require BDPA use specific to the organization, as the technology comes to reflect the properties of the organization and the wider social environment for which its designers originally intended. BDPA is, thus, not easily transferrable among collaborating RSC organizations and requires managerial attention to the institutional context within which its usage takes place. Originality/value The literature describes why organizations will use BDPA but fails to provide adequate insight into how BDPA use occurs. The authors address the “how” and bring a social perspective into a technology-centric area

An Agent-based approach to modelling integrated product teams undertaking a design activity.

The interactions between individual designers, within integrated product teams, and the nature of design tasks, all have a significant impact upon how well a design task can be performed, and hence the quality of the resultant product and the time in which it can be delivered. In this paper we describe an ongoing research project which aims to model integrated product teams through the use of multi-agent systems. We first describe the background and rationale for our work, and then present our initial computational model and results from the simulation of an integrated product team. The paper concludes with a discussion of how the model will evolve to improve the accuracy of the simulation

Effectiveness of Corporate Social Media Activities to Increase Relational Outcomes

This study applies social media analytics to investigate the impact of different corporate social media activities on user word of mouth and attitudinal loyalty. We conduct a multilevel analysis of approximately 5 million tweets regarding the main Twitter accounts of 28 large global companies. We empirically identify different social media activities in terms of social media management strategies (using social media management tools or the web-frontend client), account types (broadcasting or receiving information), and communicative approaches (conversational or disseminative). We find positive effects of social media management tools, broadcasting accounts, and conversational communication on public perception