11,767 research outputs found
CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap
After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in
multimedia search engines, we have identified and analyzed gaps within European research effort during our second year.
In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio-
economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown
of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on
requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the
community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our
Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as
National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core
technological gaps that involve research challenges, and âenablersâ, which are not necessarily technical research
challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal
challenges
Labour Market Information Driven, Personalized, OER Recommendation System for Lifelong Learners
In this paper, we suggest a novel method to aid lifelong learners to access
relevant OER based learning content to master skills demanded on the labour
market. Our software prototype 1) applies Text Classification and Text Mining
methods on vacancy announcements to decompose jobs into meaningful skills
components, which lifelong learners should target; and 2) creates a hybrid OER
Recommender System to suggest personalized learning content for learners to
progress towards their skill targets. For the first evaluation of this
prototype we focused on two job areas: Data Scientist, and Mechanical Engineer.
We applied our skill extractor approach and provided OER recommendations for
learners targeting these jobs. We conducted in-depth, semi-structured
interviews with 12 subject matter experts to learn how our prototype performs
in terms of its objectives, logic, and contribution to learning. More than 150
recommendations were generated, and 76.9% of these recommendations were treated
as useful by the interviewees. Interviews revealed that a personalized OER
recommender system, based on skills demanded by labour market, has the
potential to improve the learning experience of lifelong learners.Comment: This paper has been accepted to be published in the proceedings of
CSEDU 2020 by SciTePres
Recommended from our members
People-Powered Music: Using User-Generated Tags and Structure in Recommendations
Music recommenders often rely on experts to classify song facets like genre and mood, but user-generated folksonomies hold some advantages over expert classificationsâfolksonomies can reflect the same real-world vocabularies and categorizations that end users employ. We present an approach for using crowd-sourced common sense knowledge to structure user-generated music tags into a folksonomy, and describe how to use this approach to make music recommendations. We then empirically evaluate our âpeople-poweredâ structured content recommender against a more traditional recommender. Our results show that participants slightly preferred the unstructured recommender, rating more of its recommendations as âperfectâ than they did for our approach. An exploration of the reasons behind participantsâ ratings revealed that users behaved differently when tagging songs than when evaluating recommendations, and we discuss the implications of our results for future tagging and recommendation approaches
Desiderata for an Every Citizen Interface to the National Information Infrastructure: Challenges for NLP
In this paper, I provide desiderata for an interface that would enable ordinary people to properly access the capabilities of the NII. I identify some of the technologies that will be needed to achieve these desiderata, and discuss current and future research directions that could lead to the development of such technologies. In particular, I focus on the ways in which theory and techniques from natural language processing could contribute to future interfaces to the NII. Introduction The evolving national information infrastructure (NII) has made available a vast array of on-line services and networked information resources in a variety of forms (text, speech, graphics, images, video). At the same time, advances in computing and telecommunications technology have made it possible for an increasing number of households to own (or lease or use) powerful personal computers that are connected to this resource. Accompanying this progress is the expectation that people will be able to more..
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
Knowledge Organization Systems (KOS) in the Semantic Web: A Multi-Dimensional Review
Since the Simple Knowledge Organization System (SKOS) specification and its
SKOS eXtension for Labels (SKOS-XL) became formal W3C recommendations in 2009 a
significant number of conventional knowledge organization systems (KOS)
(including thesauri, classification schemes, name authorities, and lists of
codes and terms, produced before the arrival of the ontology-wave) have made
their journeys to join the Semantic Web mainstream. This paper uses "LOD KOS"
as an umbrella term to refer to all of the value vocabularies and lightweight
ontologies within the Semantic Web framework. The paper provides an overview of
what the LOD KOS movement has brought to various communities and users. These
are not limited to the colonies of the value vocabulary constructors and
providers, nor the catalogers and indexers who have a long history of applying
the vocabularies to their products. The LOD dataset producers and LOD service
providers, the information architects and interface designers, and researchers
in sciences and humanities, are also direct beneficiaries of LOD KOS. The paper
examines a set of the collected cases (experimental or in real applications)
and aims to find the usages of LOD KOS in order to share the practices and
ideas among communities and users. Through the viewpoints of a number of
different user groups, the functions of LOD KOS are examined from multiple
dimensions. This paper focuses on the LOD dataset producers, vocabulary
producers, and researchers (as end-users of KOS).Comment: 31 pages, 12 figures, accepted paper in International Journal on
Digital Librarie
- âŠ