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

An Approach for Asynchronous Awareness Support in Collaborative Non-Linear Storytelling

Workspace awareness support is mandatory for group support systems. It allows users not only to follow actions of others, but to understand and respond to any changes others make to the workspace. In this paper, we present a novel approach for asynchronous awareness support by offering different filters to retrieve relevant awareness information and visualizing the evolution of the shared artifact. We illustrate our approach with a tool for collaborative non-linear storytelling in which users can jointly create a story graph of interconnected audio files. Such a story graph is an example for a non-linear story. We describe the development of a prototype that visualizes how the collaborative story has evolved over time. We evaluate our approach for asynchronous awareness support in an experiment with 40 participants exploring story graphs of different complexity. The evaluation results show that our visualization approach helps group members to assess who has modified the shared story, how it was modified, what exactly has been modified, and when it has been modified.Multi Actor SystemsTechnology, Policy and Managemen

Literature Can: A Sociological Reading of Ngozi Chuma-Udeh's The Presidential Handshake

[EN] Decision making for farms is a complex task. Farmers have to fix the price of their production but several parameters have to be taken into account: harvesting, seeds, ground, season etc. This task is even more difficult when a group of farmers must make the decision. Generally, optimization models support the farmers to find no dominated solutions, but the problem remains difficult if they have to agree on one solution. In order to support the farmers for this complex decision we combine two approaches. We firstly generate a set of no dominated solutions thanks to a centralized optimization model. Based on this set of solution we then used a Group Decision Support System called GRUS for choosing the best solution for the group of farmers. The combined approach allows us to determine the best solution for the group in a consensual way. This combination of approaches is very innovative for the Agriculture domain.The authors acknowledge the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015. One of the authors acknowledges the partial support of the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595).Zaraté, P.; Alemany Díaz, MDM.; Del Pino, M.; Esteso, A.; Camilleri, G. (2019). How to Support Group Decision Making in Horticulture: An Approach Based on the Combination of a Centralized Mathematical Model and a Group Decision Support System. Lecture Notes in Business Information Processing. 348:83-94. https://doi.org/10.1007/978-3-030-18819-1_7S839434