Silva T.S., Thom L.H., Weber A., de Oliveira J.P.M., Fantinato M. (2018) Empirical Analysis of Sentence Templates and Ambiguity Issues for Business Process Descriptions. In: Panetto H., Debruyne C., Proper H., Ardagna C., Roman D., Meersman R. (eds) CoopIS, On the Move to Meaningful Internet Systems. OTM 2018 Conferences. OTM 2018. Lecture Notes in Computer Science, vol 11229. Springer
Business process management has become an increasingly present activity in organizations. In this context, approaches that assist in the identification and documentation of business processes are presented as relevant efforts to make organizations more competitive. To achieve these goals, business process descriptions are considered as a useful artifact in both identifying business processes and complementing business process documentation. However, approaches that automatically generate business process descriptions do not explain how the sentence templates that compose the text were selected. This selection influences the quality of the text, as it may produce ambiguous or non-recurring sentences, which could make it difficult to understand the process. In this work, we present an empirical analysis of 64 business process descriptions in order to find recurrent sentence templates and filter them for ambiguity issues. The analysis made it possible to find 101 sentence templates divided into 29 categories. In addition, 13 of the sentence templates were considered to have ambiguity issues based on the adopted criteria. These findings may support other approaches in generating process descriptions more suitable for process analysts and domain experts.
Business Process Model and Notation Natural language processing Sentence template Ambiguity
Probabilistic Ontology Reasoning in Ambient Assistance: Predicting Human Actions
Providing reminders to elderly people in their home environment, while they perform their daily activities, is considered as a user support activity, and thus a relevant topic in Active and Assisted Living (AAL) research and development. Determining such reminders implies decision-making, since the actions’ flow (behavior) usually involves probabilistic branches. An automated system needs to decide which of the next actions is the best one for the user in a given situation. Problems of this nature involve uncertainty levels that have to be dealt with. Many approaches to this problem exploit statistical data only, thus ignoring important semantic data as, for instance, are provided by Ontologies. However, ontologies do not support reasoning over uncertainty natively. In this paper, we present a probabilistic semantic model that enables reasoning over uncertainty without losing semantic information. This model will be exemplified by an extension of the Human Behavior Monitoring and Support [HBMS] approach that provides a conceptual model for representing the user’s behavior and its context in her/his living environment. The performance of this approach was evaluated using real data collected from a smart home prototype equipped with sensors. The experiments provided promising results which we will discuss regarding limits and challenges to overcome.
Authors: Gabriel Machado Lunardi ; Guilherme Medeiros Machado ; Fadi Al Machot ; Vinícius Maran ; Alencar Machado ; Heinrich C. Mayr ; Vladimir A. Shekhovtsov ; José Palazzo M. de Oliveira
O dissacarídeo de fórmula C12H22O11, obtido através da fervura e da evaporação de H2O do líquido resultante da prensagem do caule da gramínea Saccharus officinarum (Linneu, 1758) isento de qualquer outro tipo de processamento suplementar que elimine suas impurezas, quando apresentado sob a forma geométrica de sólidos de reduzidas dimensões e arestas retilíneas, configurando pirâmides truncadas de base oblonga e pequena altura, uma vez submetido a um toque no órgão do paladar de quem se disponha a um teste organoléptico, impressiona favoravelmente as papilas gustativas, sugerindo impressão sensorial equivalente provocada pelo mesmo dissacarídeo em estado bruto, que ocorre no líquido nutritivo da alta viscosidade, produzindo nos órgãos especiais existentes na Apis mellifera (Linneu, 1758). No entanto, é possível comprovar experimentalmente que esse dissacarídeo, no estado físico-químico descrito e apresentado sob aquela forma geométrica, apresenta considerável resistência a modificar apreciavelmente suas dimensões quando submetido a tensões mecânicas de compressão ao longo do seu eixo em conseqüência da pequena capacidade de deformação que lhe é peculiar.
QUANDO SE TEM MESTRADO
A sacarose extraída da cana de açúcar, que ainda não tenha passado pelo processo de purificação e refino, apresentando-se sob a forma de pequenos sólidos tronco-piramidais de base retangular, impressiona agradavelmente o paladar, lembrando a sensação provocada pela mesma sacarose produzida pelas abelhas em um peculiar líquido espesso e nutritivo. Entretanto, não altera suas dimensões lineares ou suas proporções quando submetida a uma tensão axial em conseqüência da aplicação de compressões equivalentes e opostas.
QUANDO SE TEM GRADUAÇÃO
O açúcar, quando ainda não submetido à refinação e, apresentando-se em blocos sólidos de pequenas dimensões e forma tronco-piramidal, tem sabor deleitável da secreção alimentar das abelhas; todavia não muda suas proporções quando sujeito à compressão.
QUANDO SE TEM ENSINO MÉDIO
Açúcar não refinado, sob a forma de pequenos blocos, tem o sabor agradável do mel, porém não muda de forma quando pressionado.
QUANDO SE TEM ENSINO FUNDAMENTAL
Açúcar mascavo em tijolinhos tem o sabor adocicado, mas não é macio ou flexível.
Vinícius Maran 1,3 Guilherme Medeiros Machado 1, Alencar Machado 2, Iara Augustin 2, and José Palazzo M. de Oliveira 1
1 Instituto de Informática, Universidade Federal do Rio Grande do Sul, 91540-000 Porto Alegre, Brazil 2 Centro de Tecnologia, Universidade Federal de Santa Maria, 97105-900 Santa Maria, Brazil 3 Coordenadoria Acadêmica, Universidade Federal de Santa Maria, Cachoeira do Sul, Brazil.
Abstract: Context-awareness is a key feature for ubiquitous computing scenarios applications. Currently, technologies and methodologies have been proposed for the integration of context-awareness concepts in intelligent information systems to adapt them to the execution of services, user interfaces and data retrieval. Recent research proposed conceptual modeling alternatives to the integration of the domain modeling in RDBMS and context-awareness modeling. The research described using highly expressiveness ontologies. The present work describes the UPCaD (Unified Process for Integration between Context-Awareness and Domain) methodology, which is composed of formalisms and processes to guide the data integration considering RDBMS and context modeling. The methodology was evaluated in a virtual learning environment application. The evaluation shows the possibility to use a highly expressive context ontology to filter the relational data query and discusses the main contributions of the methodology compared with recent approaches.
On behalf of the ER Steering Committee, we are pleased to announce the winner of the 2016 Peter P. Chen Award: Oscar Pastor of the Universitat Politecnica de Valencia.
Initiated by Elsevier in 2008 to celebrate the 25th anniversary of the journal Data and Knowledge Engineering, the Peter P. Chen Award honors one person each year for his or her outstanding contributions to the field of conceptual modeling. The winner will receive a prize of $2500 sponsored by Elsevier Publishing Company, and also will give a keynote speech at the ER2016 conference to be held November 14-17 in Gifu, Japan.
The selection process was done according to the following five criteria:
* Research: how well the nominee has helped advance the field of conceptual modeling with his/her intellectual contributions.
* Service: participation in the organization of conceptual-modeling-related meetings and conferences and participation in editorial boards of conceptual-modeling-related journals.
* Education: how effectively the nominee has mentored doctoral students in conceptual modeling, produced researchers from their labs, and also helped mentor young people in the field.
* Contribution to practice: the extent to which the nominee has contributed to technology transfer, commercialization, and industrial projects.
* International reputation: the extent to which the nominee’s work is visible to and has diffused into the international community.
The 2016 selection committee consisted of Stephen Liddle, Heinrich Mayr, Carlo Batini, Tok Wang Ling, and Il-Yeol Song. The committee reviewed the qualifications of the nominees, and chose Professor Pastor because he “has been a towering figure in the field of conceptual modeling for more than two decades”. Prof. Pastor has contributed both through research and service to the community, and his work has had an impact both on research and practice. On all of the criteria dimensions (research, service, education, practice, reputation), Oscar Pastor is exemplary. He was previously recognized as an ER Fellow in 2010. We extend our congratulations and best wishes to Dr. Pastor and his family.
Winners of the Peter P. Chen Award include:
2016 Oscar Pastor, Universitat Politecnica de Valencia, Spain
2015 Il-Yeol Song, Drexel University, USA
2014 Antonio L. Furtado, Pontificia Univ. Catolica do Rio de Janeiro, Brazil
2013 Carlo Batini, Universita degli Studi di Milano-Bicocca, Italy
2012 Stefano Spaccapietra, Ecole Polytechnique Federale de Lausanne, Switzerland
2011 Tok Wang Ling, National University of Singapore, Singapore
2010 John Mylopoulos, University of Trento, Italy
2009 David Embley, Brigham Young University, USA
2008 Bernhard Thalheim, University of Kiel, Germany