7,937 research outputs found
Transforming Wikipedia into an Ontology-based Information Retrieval Search Engine for Local Experts using a Third-Party Taxonomy
Wikipedia is widely used for finding general information about a wide variety
of topics. Its vocation is not to provide local information. For example, it
provides plot, cast, and production information about a given movie, but not
showing times in your local movie theatre. Here we describe how we can connect
local information to Wikipedia, without altering its content. The case study we
present involves finding local scientific experts. Using a third-party
taxonomy, independent from Wikipedia's category hierarchy, we index information
connected to our local experts, present in their activity reports, and we
re-index Wikipedia content using the same taxonomy. The connections between
Wikipedia pages and local expert reports are stored in a relational database,
accessible through as public SPARQL endpoint. A Wikipedia gadget (or plugin)
activated by the interested user, accesses the endpoint as each Wikipedia page
is accessed. An additional tab on the Wikipedia page allows the user to open up
a list of teams of local experts associated with the subject matter in the
Wikipedia page. The technique, though presented here as a way to identify local
experts, is generic, in that any third party taxonomy, can be used in this to
connect Wikipedia to any non-Wikipedia data source.Comment: Joint Second Workshop on Language and Ontology \& Terminology and
Knowledge Structures (LangOnto2 + TermiKS) LO2TKS, May 2016, Portoroz,
Slovenia. 201
Participatory Transformations
Learning, in its many forms, from the classroom to independent study, is being transformed by new practices emerging around Internet use. Conversation, participation and community have become watchwords for the processes of learning promised by the Internet and accomplished via technologies such as bulletin boards, wikis, blogs, social software and repositories, devices such as laptops, cell phones and digital cameras, and infrastructures of internet connection, telephone, wireless and broadband. This chapter discusses the impact of emergent, participatory trends on education. In learning and teaching participatory trends harbinge a radical transformation in who learns from whom, where, under what circumstances, and for what and whose purpose. They bring changes in where we find information, who we learn from, how learning progresses, and how we contribute to our learning and the learning of others. These trends indicate a transformation to "ubiquitous learning" ??? a continuous anytime, anywhere, anyone contribution and retrieval of learning materials and advice on and through the Internet and its technologies, niches and social spaces.not peer reviewe
Possibilities of quality enhancement in higher education by intensive use of information technology
Quality of higher education is a multi-dimensional concept. It lies in effectiveness of transmitting knowledge and skill; the authenticity, content, coverage and depth of information; availability of reading/teaching materials; help in removing obstacles to learning; applicability of knowledge in solving the real life problems; fruitfulness of knowledge in personal and social domains; convergence of content and variety of knowledge over space (countries and regions) and different sections of the people; cost-effectiveness and administrative efficiency. Information technology has progressed very fast in the last three decades; it has produced equipments at affordable cost and it has now made their wider application feasible. This technology has made search, gathering, dissemination, storing, retrieval, transmission and reception of knowledge easier, cheaper and faster. Side by side, a vast virtual library vying with the library in prints has emerged and continues growing rapidly. One may hold that the e-libraries are the libraries of tomorrow when the libraries in prints will be the antiques or the archival objects of the past. This paper discusses in details how information technology can be applied to enhance the quality of higher education at affordable cost. It also discusses the major obstacles to optimal utilization of information technology and measures to remove them.Information Technology; Quality in Higher Education; e-library; e-book; e-journal
A virtue epistemology of the Internet: Search engines, intellectual virtues and education
This paper applies a virtue epistemology approach to using the Internet, as to improve our information-seeking behaviours. Virtue epistemology focusses on the cognitive character of agents and is less concerned with the nature of truth and epistemic justification as compared to traditional analytic epistemology. Due to this focus on cognitive character and agency, it is a fruitful but underexplored approach to using the Internet in an epistemically desirable way. Thus, the central question in this paper is: How to use the Internet in an epistemically virtuous way? Using the work of Jason Baehr, it starts by outlining nine intellectual or epistemic virtues: curiosity, intellectual autonomy, intellectual humility, attentiveness, intellectual carefulness, intellectual thoroughness, open-mindedness, intellectual courage and intellectual tenacity. It then explores how we should deploy these virtues and avoid the corresponding vices when interacting with the Internet, particularly search engines. Whilst an epistemically virtuous use of the Internet will not guarantee that one will acquire true beliefs, understanding or even knowledge, it will strongly improve one’s information-seeking behaviours. The paper ends with arguing that teaching and assessing online intellectual virtues should be part of school and university curricula, perhaps embedded in critical thinking courses, or even better, as individual units
Toward a collective intelligence recommender system for education
The development of Information and Communication Technology (ICT), have revolutionized the world and have moved us into the information age, however the access and handling of this large amount of information is causing valuable time losses. Teachers in Higher Education especially use the Internet as a tool to consult materials and content for the development of the subjects. The internet has very broad services, and sometimes it is difficult for users to find the contents in an easy and fast way. This problem is increasing at the time, causing that students spend a lot of time in search information rather than in synthesis, analysis and construction of new knowledge. In this context, several questions have emerged: Is it possible to design learning activities that allow us to value the information search and to encourage collective participation?. What are the conditions that an ICT tool that supports a process of information search has to have to optimize the student's time and learning?
This article presents the use and application of a Recommender System (RS) designed on paradigms of Collective Intelligence (CI). The RS designed encourages the collective learning and the authentic participation of the students.
The research combines the literature study with the analysis of the ICT tools that have emerged in the field of the CI and RS. Also, Design-Based Research (DBR) was used to compile and summarize collective intelligence approaches and filtering techniques reported in the literature in Higher Education as well as to incrementally improving the tool.
Several are the benefits that have been evidenced as a result of the exploratory study carried out. Among them the following stand out:
• It improves student motivation, as it helps you discover new content of interest in an easy way.
• It saves time in the search and classification of teaching material of interest.
• It fosters specialized reading, inspires competence as a means of learning.
• It gives the teacher the ability to generate reports of trends and behaviors of their students, real-time assessment of the quality of learning material.
The authors consider that the use of ICT tools that combine the paradigms of the CI and RS presented in this work, are a tool that improves the construction of student knowledge and motivates their collective development in cyberspace, in addition, the model of Filltering Contents used supports the design of models and strategies of collective intelligence in Higher Education.Postprint (author's final draft
Explainable Patterns: Going from Findings to Insights to Support Data Analytics Democratization
In the past decades, massive efforts involving companies, non-profit
organizations, governments, and others have been put into supporting the
concept of data democratization, promoting initiatives to educate people to
confront information with data. Although this represents one of the most
critical advances in our free world, access to data without concrete facts to
check or the lack of an expert to help on understanding the existing patterns
hampers its intrinsic value and lessens its democratization. So the benefits of
giving full access to data will only be impactful if we go a step further and
support the Data Analytics Democratization, assisting users in transforming
findings into insights without the need of domain experts to promote
unconstrained access to data interpretation and verification. In this paper, we
present Explainable Patterns (ExPatt), a new framework to support lay users in
exploring and creating data storytellings, automatically generating plausible
explanations for observed or selected findings using an external (textual)
source of information, avoiding or reducing the need for domain experts. ExPatt
applicability is confirmed via different use-cases involving world demographics
indicators and Wikipedia as an external source of explanations, showing how it
can be used in practice towards the data analytics democratization.Comment: 8 Figures, 10 pages, submitted to VIS 202
Breaking Sticks and Ambiguities with Adaptive Skip-gram
Recently proposed Skip-gram model is a powerful method for learning
high-dimensional word representations that capture rich semantic relationships
between words. However, Skip-gram as well as most prior work on learning word
representations does not take into account word ambiguity and maintain only
single representation per word. Although a number of Skip-gram modifications
were proposed to overcome this limitation and learn multi-prototype word
representations, they either require a known number of word meanings or learn
them using greedy heuristic approaches. In this paper we propose the Adaptive
Skip-gram model which is a nonparametric Bayesian extension of Skip-gram
capable to automatically learn the required number of representations for all
words at desired semantic resolution. We derive efficient online variational
learning algorithm for the model and empirically demonstrate its efficiency on
word-sense induction task
CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines
Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective.
The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines.
From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research
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