A debate dashboard to enhance on-line knowledge sharing

Purpose – Web 2.0 technologies have radically modified the way in which knowledge is created, managed and shared, improving productivity and accelerating innovation processes for the enterprises. These technologies have allowed enterprises to produce knowledge, leverage collective intelligence and build social capital on a scale that was unimaginable a few years ago. In this paper we focus on a particular kind of web-based collaborative platforms known as argument mapping tools and we discuss the main barriers to the adoption of them. Literature has proved that these argument mapping tools provide large and small and medium enterprise with several advantages, but nevertheless, they have low level adoption. In this paper we explore new technological solutions to support the adoption of argument mapping tools. In particular, we propose the design of a Debate Dashboard to provide visual feedback to support online deliberation. These visual feedback aims at compensating the loss of information due to the mediation of the technology. The Debate Dashboard is composed of a set of suitable visualization tools that have been selected on the basis of a literature review of the visualization tools. Design/methodology/approach - We propose a literature review of existing visualization tools. Building on the literature review we selected thirty visualization tools, which have been classified on the basis of the kind of feedback they are able to provide. We identify three classes of feedback: Community feedback (identikit of users), Interaction feedback (about how users interact) and Absorption feedback (about generated content and its organization). We distilled the Debate Dashboard features by building on results of a literature review on Web 2.0 tools for data visualization. As output of literature review we selected six visualization tools. We consider these selected tools as a sort of starting point. Indeed, our aim is the improvement of them through the addition of further features and functions in order to make them more effective in providing feedback. Originality/value – Our paper enriches the debate about computer mediated conversation and visualization tools. We propose a Dashboard prototype to augment collaborative knowledge mapping tools by providing visual feedback on conversations. The Dashboard will provide at the same time three different kinds of feedback about: details of the participants to the conversation, interaction processes and generated content. This will allow the improvement of the benefits and reduce the costs deriving from the use of mapping tools. Moreover, another important novelty is that visualization tools will be integrated to mapping tools, as until now they have been used only to visualize data contained in forums (as Usenet or Slash.dot), chat or email archives Practical implications – The Dashboard provides feedback about participants, interaction processes and generated contents, thus supporting the adoption of mapping tools as technologies able to foster knowledge sharing among remote workers or/and customers and supplier. The integration of Debate Dashboard with common online argument mapping tools aims at enabling the following advantages: 1. Reduction of misunderstanding; 2. Reduction of cognitive effort required to use argument mapping tools; 3. Improvement of the exploration and the analysis of the maps - the Debate Dashboard feedback improves the usability of the object (the map), thus allowing users to pitch into the conversation in the right place

Deep Learning based Recommender System: A Survey and New Perspectives

With the ever-growing volume of online information, recommender systems have been an effective strategy to overcome such information overload. The utility of recommender systems cannot be overstated, given its widespread adoption in many web applications, along with its potential impact to ameliorate many problems related to over-choice. In recent years, deep learning has garnered considerable interest in many research fields such as computer vision and natural language processing, owing not only to stellar performance but also the attractive property of learning feature representations from scratch. The influence of deep learning is also pervasive, recently demonstrating its effectiveness when applied to information retrieval and recommender systems research. Evidently, the field of deep learning in recommender system is flourishing. This article aims to provide a comprehensive review of recent research efforts on deep learning based recommender systems. More concretely, we provide and devise a taxonomy of deep learning based recommendation models, along with providing a comprehensive summary of the state-of-the-art. Finally, we expand on current trends and provide new perspectives pertaining to this new exciting development of the field.Comment: The paper has been accepted by ACM Computing Surveys. https://doi.acm.org/10.1145/328502

The links between international production and innovation: a double network approach

This paper examines the changing role of multinationals in the global generation, adoption and transfer of innovation. It is argued that the combination of traditional asset exploiting objectives with increasing asset seeking activities entails a transition of multinationals towards a double network structure. On the one hand multinationals are more and more characterised by the interconnection of a large number of internal units that are deeply involved in the company’s use, generation and absorption of knowledge. On the other hand, units belonging to the internal network tend to develop external networks with other firms and institutions that are located outside the boundaries of the multinational firm, in order to increase the potential for use, generation and absorption of knowledge. Extending the analysis to a more general level, it is suggested that each of the external actors with which multinationals are interconnected across countries are themselves involved in extensive webs of relationships with other firms and institutions. By becoming embedded in different local contexts, multinational firms act as bridging institutions connecting a number of geographically dispersed economic and innovation systems. As a result, they are conditioned by, and contribute to, the evolution of different contexts in which they operate.innovation, multinational firms, networks.

Web-based support for managing large collections of software artefacts

There has been a long history of CASE tool development, with an underlying software repository at the heart of most systems. Usually such tools, even the more recently web-based systems, are focused on supporting individual projects within an enterprise or across a number of distributed sites. Little support for maintaining large heterogeneous collections of software artefacts across a number of projects has been developed. Within the GENESIS project, this has been a key consideration in the development of the Open Source Component Artefact Repository (OSCAR). Its most recent extensions are explicitly addressing the provision of cross project global views of large software collections as well as historical views of individual artefacts within a collection. The long-term benefits of such support can only be realised if OSCAR is widely adopted and various steps to facilitate this are described