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Publicações

Publicações por HumanISE

2017

Mobile Augmented Reality in Cultural Heritage Context: Current Technologies

Autores
Marto, AGR; Augusto de Sousa, AA; Marques Goncalves, AJM;

Publicação
2017 24 ENCONTRO PORTUGUES DE COMPUTACAO GRAFICA E INTERACAO (EPCGI)

Abstract
The use of augmented reality has a great potential applied to several areas, in particular, for cultural heritage context where it became possible to display, in loco, virtual elements which complement the user's real scenario. Due to technological advances, differentiated ways of experience this technology has been explored, providing to common user, the access to this technology, until recently, quite limited, especially, in public locations. This article presents a work which includes implementation and evaluation of distinct applications of augmented reality - using smartphones - based on different techniques and tools. The evaluation intends to identify a solution to be implemented in a cultural heritage context, namely, the ruins of the Museu Monografico de Conimbriga

2017

Effects of Language and Terminology of Query Suggestions on Medical Accuracy Considering Different User Characteristics

Autores
Lopes, CT; Paiva, D; Ribeiro, C;

Publicação
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY

Abstract
Searching for health information is one of the most popular activities on the web. In this domain, users often misspell or lack knowledge of the proper medical terms to use in queries. To overcome these difficulties and attempt to retrieve higher-quality content, we developed a query suggestion system that provides alternative queries combining the Portuguese or English language with lay or medico-scientific terminology. Here we evaluate this system's impact on the medical accuracy of the knowledge acquired during the search. Evaluation shows that simply providing these suggestions contributes to reduce the quantity of incorrect content. This indicates that even when suggestions are not clicked, they are useful either for subsequent queries' formulation or for interpreting search results. Clicking on suggestions, regardless of type, leads to answers with more correct content. An analysis by type of suggestion and user characteristics showed that the benefits of certain languages and terminologies are more perceptible in users with certain levels of English proficiency and health literacy. This suggests a personalization of this suggestion system toward these characteristics. Overall, the effect of language is more preponderant than the effect of terminology. Clicks on English suggestions are clearly preferable to clicks on Portuguese ones.

2017

Involving data creators in an ontology-based design process for metadata models

Autores
Castro, JA; Amorim, RC; Gattelli, R; Karimova, Y; Da Silva, JR; Ribeiro, C;

Publicação
Developing Metadata Application Profiles

Abstract
Research data are the cornerstone of science and their current fast rate of production is disquieting researchers. Adequate research data management strongly depends on accurate metadata records that capture the production context of the datasets, thus enabling data interpretation and reuse. This chapter reports on the authors' experience in the development of the metadata models, formalized as ontologies, for several research domains, involving members from small research teams in the overall process. This process is instantiated with four case studies: vehicle simulation; hydrogen production; biological oceanography and social sciences. The authors also present a data description workflow that includes a research data management platform, named Dendro, where researchers can prepare their datasets for further deposit in external data repositories. © 2017, IGI Global.

2017

Predicting the Situational Relevance of Health Web Documents

Autores
Oroszlanyova, M; Lopes, CT; Nunes, S; Ribeiro, C;

Publicação
2017 12TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI)

Abstract
Relevance is usually estimated by search engines using document content, disregarding the user behind the search and the characteristics of the task. In this work, we look at relevance as framed in a situational context, calling it situational relevance, and analyze if it is possible to predict it using documents, users and tasks characteristics. Using an existing dataset composed of health web documents, relevance judgments for information needs, user and task characteristics, we build a multivariate prediction model for situational relevance. Our model has an accuracy of 77.17%. Our findings provide insights into features that could improve the estimation of relevance by search engines, helping to conciliate the systemic and situational views of relevance. In a near future we will work on the automatic assessment of document, user and task characteristics.

2017

Promoting Semantic Annotation of Research Data by Their Creators: A Use Case with B2NOTE at the End of the RDM Workflow

Autores
Karimova, Y; Castro, JA; da Silva, JR; Pereira, N; Ribeiro, C;

Publicação
Metadata and Semantic Research - 11th International Conference, MTSR 2017 Tallinn, Estonia, November 28 - December 1, 2017, Proceedings

Abstract
Research data management is promoted at different levels with awareness actions carried out to encourage cooperation between researchers. However, data management requires tools to set the scene for researchers and institutions to disseminate the research data they produce. In this context good quality metadata play an important role by enabling data reuse. EUDAT is an European common data infrastructure, with integrated services for data preservation and dissemination. The TAIL project, at the University of Porto, proposes workflows based on Dendro, a collaborative environment that helps researchers prepare well described datasets and deposit them in a data repository. We propose a data deposit workflow use case for a small research project with emphasis in data annotation. Data is organized and described in Dendro; deposited in B2SHARE; and semantic annotation is performed with the new B2NOTE service from EUDAT. © Springer International Publishing AG 2017.

2017

People who borrowed this have also borrowed: recommender system in academic library

Autores
Krebs, LM; da Rocha, RP; Ribeiro, C;

Publicação
PERSPECTIVAS EM CIENCIA DA INFORMACAO

Abstract
The paper analises the use of recommender systems in academic libraries, examining the use of the " Related books in Aleph OPAC" recommendation system for academic libraries' online catalogues. A quantitative approach and descriptive methodology is used to collect, process and analyse the data from a usage log provided by the University of Dundee. The analysis of 13,654 posts and 6,347 sessions provided the following observations: the recommendation was used in 11% of the sessions, and 43.9% of the recorded document views on those sessions where generated by recommendation. 9.6% of the records of document views, were derived from recommendation. Sessions using recommendations were on average 1 minute 18 seconds shorter than the sessions without recommendations. In sessions with recommendation 4.30 records were viewed on average while in sessions without recommendation the average is 1.88. Using more than one type of recommendation is not common, as 82% of the sessions with recommendation have recorded the use of only one kind of recommendation. The analysis of recommendations by kind provided two results: "Related works include" appears in more sessions (348), while " People who borrowed this work also borrowed" has the highest number of posts (584).

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