75 research outputs found
Discovering prerequisite relations from educational documents through word embeddings
No full textInferring prerequisite relations among educational documents, in terms of prior knowledge required to understand and complete assignments about certain topics, is a crucial task for instructional designers and teachers. Massive open online courses, electronic textbooks, public encyclopedias and repositories of learning objects and other forms of informative content create a huge availability of educational material, which can be exploited in online platforms for distance education, both for recommending specific resources and personalized learning paths. But public taxonomies of prerequisites, or learning object metadata useful to trace down prerequisites are not generally available. A description of a new approach for prerequisite discovering in educational documents is given. It is based on word embeddings, that is, statistical language models for the representation of text-based learning objects in low-dimensional latent spaces. It takes advantage of the latent representations to identify prerequisites in a binary classification setting. The accuracy of the approach is validated by means of an experimental benchmark covering multiple datasets of educational material
Using Graph Embedding to Monitor Communities of Learners
No full textHow to keep track of the learning process of a community of learners is a problem whose resolution requires accurate assessment tools and appropriate teaching and learning strategies. Peer Assessment is a standard didactic strategy which requires students in a course to correct their peers’ assignments. Since the representation of a community, even a large one, of students, is based on directed graphs, it is difficult to follow its whole dynamics. In this paper, we investigate the possibility of using two machine learning techniques: Graph Embeddings, and Principal Component Analysis, to represent a students’ communities by points in a 2D space, in order to have valuable and understandable information on the dynamics of the group. For this purpose we present a case study based on three real Peer Assessment sessions. The first results are encouraging
A Web-based Training System for Business Letter Writing
No full textAs with the growing degree of office automation and diffuse use of electronic media, such as e-mails, written business communication is becoming a key element to promote synergies, relationships and disseminating information about products and services. Task recognition and the definition of strategies and suitable vocabularies are some of the activities that office workers deal with each time a communicative intent has to be effectively transferred and understood by a given addressee. This paper introduces a web-based intelligent training system based on the constructivism theory and self-directed learning paradigms for assisting company workers in the drafting business letters-writing task. A case-based engine suggests ad hoc rhetorical letters that users have the chance to adapt to their particular contexts and save them into user-defined case libraries
Personalized weight loss strategies by mining activity tracker data
No full textWearable devices make self-monitoring easier by the users, who usually tend to increase physical activity and weight loss maintenance over time. But in terms of behavior adaptation to these goals, these devices do not provide specific features beyond monitoring the achievement of daily goals, such as a number of steps or miles walked and caloric outtake. The purpose of this study is twofold. By analyzing a large dataset of signals collected by these devices, we identify significant clusters of similar behavior patterns related to user physical activities. We then examine specific patterns of step count in the context of recommendation of habits that more likely give rise to weight loss effects. The evaluation of the effectiveness of these personalized recommendations, based on a comparative study, proves how a recommender system based on the reinforcement learning paradigm is able to guarantee better performance for this task by balancing the trade-off between long-term and short-term rewards
A Web-based Training System for Business Letter Writing
No full textAs with the growing degree of office automation and diffuse use of electronic media, such as e-mails, written business communication is becoming a key element to promote synergies, relationships and disseminating information about products and services. Task recognition and the definition of strategies and suitable vocabularies are some of the activities that office workers deal with each time a communicative intent has to be effectively transferred and understood by a given addressee. This paper introduces a web-based intelligent training system based on the constructivism theory and self-directed learning paradigms for assisting company workers in the drafting business letters-writing task. A case-based engine suggests ad hoc rhetorical letters that users have the chance to adapt to their particular contexts and save them into user-defined case libraries
Finding Information on the Web: Enhancing Traditional Methodologies
No full textand Information Overloading are phenomena that
frequently occur when users look for information and
interact with many information sources.
In this paper, two innovative search algorithms will be
proposed. Their aim is to autonomously search information
about a particular topic, in huge hypertextual collections,
such as the Web. Starting from a little resource set, e.g.,
bookmarks or references in some categories of directory
services, the algorithms select interactively the links which
have the potentiality to reach new interesting resources for
the user.
We argue that the information systems based on the
proposed algorithms may successfully facilitate the users’
interaction with the present Information and
Communication Technologies, addressing problems as
Information Overloading and the Misleading Information
Mining social networks for local search and location-based recommender systems (Editorial)
No full textLocation-based services (LBSs) are software-level services that use location data in order to provide interesting and useful content to users or other services. The widespread usage of smartphones and wearable devices has made available large amounts of spatio-temporal data (e.g., geolocation, motion and environmental sensors)..
Il patrimonio del fondo Gasparetti dell'Università Cattolica di Milano e l'importanza della sua eredità culturale per l'ispanismo italiano
No full textAntonio Gasparetti fue profesor de literatura española y traductor de muchas obras literarias del español al italiano para las editoriales Rizzoli, Einaudi y Morcelliana desde los años Cuarenta hasta los años Setenta del siglo pasado. Discípulo del célebre hispanista Antonio Restori, trabajó también como crítico literario, centrándose sobre todo en el estudio de los principales autores de los Siglos de Oro y de la Edad de Plata. Después de su fallecimiento, en 1989 sus herederos decidieron legar a la Universidad Católica de Milán una parte de los ricos fondos bibliográficos y otros documentos de su biblioteca personal. Dichos fondos constan de 1309 volúmenes que presentan carácter multidisciplinar y abarcan contribuciones que van de algunos impresos fechados Siglos XVII y XVIII hasta monografías de más reciente publicación relacionadas con el análisis de diferentes aspectos de la literatura española. Este artículo pretende reflexionar sobre la figura del hispanista Gasparetti para subrayar el valor que su personal contribución ha tenido para el desarrollo de los estudios hispánicos en Italia. Al mismo tiempo, el trabajo se propone realizar una descripción bibliográfica de la colección con el fin de proporcionar datos más específicos y ordenar las informaciones acerca del fondo mismo que representa uno de los ejemplos más significativos de la conexión cultural entre España e Italia
Tourism Recommender Systems as a Vehicle for Social and Cultural Inclusion
No full textRecommender systems for tourism have become so popular that our smart phones are now full of applications that can suggest customized itineraries anywhere and anytime. Most of them, however, recommend similar itineraries, usually even in the same overcrowded areas. In this article, we present the concept of an integrated framework for cultural tourism with different characteristics. Such a framework can propose alternative customized itineraries to favor cultural and social inclusion of visitors with local residents, for example, in urban suburbs or agricultural and industrial regions. Therefore, the system has to provide user interfaces to enable organizations, local enterprises, and visitors to analyze and exploit rich open data sources. In this way, local institutions could better plan and handle cultural tourism and public resources. Small businesses could cost-effectively promote their services. Visitors could receive personalized routes with knowledge related to local communities, cultures, traditions, and others. © 202
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