Segmentation of lecture videos based on text: A method combining multiple linguistic features

In multimedia-based e-Learning systems, there are strong needs for segmenting lecture videos into topic units in order to organize the videos for browsing and to provide search capability. Automatic segmentation is highly desired because of the high cost of manual segmentation. While a lot of research has been conducted on topic segmentation of transcribed spoken text, most attempts rely on domain-specific cues and formal presentation format, and require extensive training; none of these features exist in lecture videos with unscripted and spontaneous speech. In addition, lecture videos usually have few scene changes, which implies that the visual information that most video segmentation methods rely on is not available. Furthermore, even when there are scene changes, they do not match with the topic transitions. In this paper, we make use of the transcribed speech text extracted from the audio track of video to segment lecture videos into topics. We review related research and propose a new segmentation approach. Our approach utilizes features such as noun phrases and combines multiple content-based and discourse-based features. Our preliminary results show that the noun phrases are salient features and the combination of multiple features is promising to improve segmentation accuracy.published_or_final_versio

Pro-active Meeting Assistants: Attention Please!

This paper gives an overview of pro-active meeting assistants, what they are and when they can be useful. We explain how to develop such assistants with respect to requirement definitions and elaborate on a set of Wizard of Oz experiments, aiming to find out in which form a meeting assistant should operate to be accepted by participants and whether the meeting effectiveness and efficiency can be improved by an assistant at all. This paper gives an overview of pro-active meeting assistants, what they are and when they can be useful. We explain how to develop such assistants with respect to requirement definitions and elaborate on a set of Wizard of Oz experiments, aiming to find out in which form a meeting assistant should operate to be accepted by participants and whether the meeting effectiveness and efficiency can be improved by an assistant at all

Prediction of Ideas Number During a Brainstorming Session

International audienceIn this paper, we present an approach allowing the prediction of ideas number during a brainstorming session. This prediction is based on two dynamic models of brainstorming, the non-cognitive and the cognitive models proposed by Brown and Paulus (Small Group Res 27(1):91–114, 1996). These models describe for each participant, the evolution of ideas number over time, and are formalized by differential equations. Through solution functions of these models, we propose to calculate the number of ideas of each participant on any time intervals and thus in the future (called prediction). To be able to compute solution functions, it is necessary to determine the parameters of these models. In our approach, we use optimization model for model parameters calculation in which solution functions are approximated by numerical methods. We developed two generic optimization models, one based on Euler’s and the other on the fourth order Runge–Kutta’s numerical methods for the solving of differential equations, and we apply them to the non-cognitive and respectively to the cognitive models. Through some feasibility tests, we show the adequacy of the proposed approach to our prediction context

Group support systems features and their contribution to technology strategy decision-making: A review and analysis

Collective decision-making processes require careful design considerations in organizations. On one hand, the inclusion of a greater number of actors contribute to a wider knowledge base, on the other, it can become a diffuse process and be distorted from the principles initially established. This paper observes a specific collective decision making process in organizations—technology strategy formulation—and, through a critical review of the literature, analyzes how the advances in features of group support systems support improvements in different stages of this process. This paper also discusses the implications of GSS appropriation in group dynamics.This research was supported by Fundação para a Ciência e Tecnologia (SFRH/ BD/ 33727/ 2009), within the framework of the MIT Portugal Program.info:eu-repo/semantics/publishedVersio

Designing the digital organization

Abstract Increasingly, organizations are assessing their opportunities, developing and delivering products and services, and interacting with customers and other stakeholders digitally. Mobile computing, social media, and big data are the drivers of the future workplace, and these and other digitally based technologies are having large economic and social impacts, including increased competition and collaboration, the disruption of many industries, and pressure being put on organizations to develop new capabilities and transform their cultures. In this article, we provide a conceptual framework for the design of effective digital organizations. Our framework is predicated on the current state of digitization across diverse sectors of the global economy. In the digital world, all activities and transactions leave digital marks, and all actors, things, and places can be reached and affected digitally. As a result, we can design for self-organization rather than using hierarchical mechanisms for control and coordination. Such designs require the strategic and cultural alignment of digital technologies within the organization and externally with stakeholders. We propose that “actor-oriented” principles are at the heart of designing digital organizations and that, if properly applied, can result in a workplace where organization members are highly engaged and productive