A social software/Web 2.0 approach to collaborative knowledge engineering

Richards, Deborah

doi:10.1016/j.ins.2009.01.031

Cited by 59 publications

(47 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…14 In the context of RDR systems, collaborative knowledge acquisition was demonstrated as a promising technique for the prompt construction of knowledge bases. 8 While in this study we used a very simple method of collaborative filtering to identify relevant features and combine input from the internists, in a future system we could improve performance by employing more sophisticated methods.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Collaborative knowledge acquisition for the design of context-aware alert systems

Joffe

Havakuk

Herskovic

et al. 2012

J Am Med Inform Assoc

View full text Add to dashboard Cite

Objective To present a framework for combining implicit knowledge acquisition from multiple experts with machine learning and to evaluate this framework in the context of anemia alerts. Materials and Methods Five internal medicine residents reviewed 18 anemia alerts, while 'talking aloud'. They identified features that were reviewed by two or more physicians to determine appropriate alert level, etiology and treatment recommendation. Based on these features, data were extracted from 100 randomlyselected anemia cases for a training set and an additional 82 cases for a test set. Two staff internists assigned an alert level, etiology and treatment recommendation before and after reviewing the entire electronic medical record. The training set of 118 cases (100 plus 18) and the test set of 82 cases were explored using RIDOR and JRip algorithms. Results The feature set was sufficient to assess 93% of anemia cases (intraclass correlation for alert level before and after review of the records by internists 1 and 2 were 0.92 and 0.95, respectively). High-precision classifiers were constructed to identify low-level alerts (precision p¼0.87, recall R¼0.4), iron deficiency (p¼1.0, R¼0.73), and anemia associated with kidney disease (p¼0.87, R¼0.77). Discussion It was possible to identify low-level alerts and several conditions commonly associated with chronic anemia. This approach may reduce the number of clinically unimportant alerts. The study was limited to anemia alerts. Furthermore, clinicians were aware of the study hypotheses potentially biasing their evaluation. Conclusion Implicit knowledge acquisition, collaborative filtering and machine learning were combined automatically to induce clinically meaningful and precise decision rules. BACKGROUND AND SIGNIFICANCE

show abstract

Section: Discussionmentioning

confidence: 99%

“…RDR systems have been successfully implemented in various fields (laboratory results, calls centers, email management, etc. ), 7 have been expanded to include collaborative input from multiple experts, 8 and have been integrated with machine learning. 9 10 However, these systems all require explicit expert input.…”

Section: Model Formulationmentioning

confidence: 99%

Collaborative knowledge acquisition for the design of context-aware alert systems

Joffe

Havakuk

Herskovic

et al. 2012

J Am Med Inform Assoc

View full text Add to dashboard Cite

show abstract

“…Os gerentes podem capturar o conhecimento informal em redes sociais e aprender sobre como interagir para colaborar em grupos de trabalho (RICHARDS, 2009). Os softwares de MS desafiam o pensamento estratégico para a criatividade, independência e desempenho em ambientes incertos, porque ajudam a converter parte do conhecimento tácito em conhecimento explícito (HAEFLIGER et al, 2011).…”

Section: Gestão Do Conhecimento (Gc) E Mídias Sociais (Ms)unclassified

Gestão Do Conhecimento E Mídias Sociais: Método De Busca De Informações Confiáveis Para Incentivar Pesquisas Futuras

Valentim¹,

Vignochi²,

Lezana³

2017

ALCANCE

View full text Add to dashboard Cite

Redes sociais corporativas compreendem interações imersas em um ambiente de ferramentas de mídias sociais. As empresas precisam entender a globalização impulsionada pela tecnologia da informação, sua influência na Gestão do Conhecimento e como usar Mídias Sociais para sobreviver e ganhar vantagem competitiva. O objetivo deste estudo é identificar como a Gestão do Conhecimento e as Mídias Sociais estão relacionadas na literatura científica para encorajar futuras pesquisas. O método de mapeamento de conhecimento científico denominado Processo Construtivista de Desenvolvimento de Conhecimento (ProKnow-C) apoiou uma análise bibliométrica e sistêmica de literatura. O ProKnow-C é uma opção para selecionar publicações científicas confiáveis segundo sua relevância. A análise dos dados exibe 42 artigos na base Science Direct entre janeiro de 2005 e fevereiro de 2017. Mostra as principais revistas, descreve conceitos e identifica metodologias utilizadas em artigos sobre Gestão do Conhecimento e Mídias Sociais. O ProKnow-C viabilizou buscar, organizar e analisar dados bibliográficos em conformidade com uma base de dados confiáveis. Na análise dos resultados identificaram-se lacunas e oportunidades de pesquisas futuras. Estudos em profundidade serão úteis para a perspectiva estratégica das corporações nas seguintes direções: influência nos ambientes interno e externo, identificação de ferramentas simples e úteis, razões da desistência de uso e influência de aspectos comportamentais e psicológicos sobre usuários.

show abstract

“…In (Richards, 2009), for example, a knowledge engineering approach which offers wiki-style collaboration is introduced, aiming to facilitate the capture of knowledge-in-action which spans both explicit and implicit knowledge types. The approach extends a combined rule and case-based knowledge acquisition technique, known as Multiple Classification Ripple Down Rules, to allow multiple users to collaboratively view, define and refine a knowledge base over time and space.…”

Section: Wiki-based Collaborative Knowledge Engineeringmentioning

confidence: 99%

Open Praxis, volume 6 issue 2

Gil‐Jaurena¹

2014

Open Praxis

View full text Add to dashboard Cite

A social software/Web 2.0 approach to collaborative knowledge engineering

Cited by 59 publications

References 13 publications

Collaborative knowledge acquisition for the design of context-aware alert systems

Collaborative knowledge acquisition for the design of context-aware alert systems

Gestão Do Conhecimento E Mídias Sociais: Método De Busca De Informações Confiáveis Para Incentivar Pesquisas Futuras

Open Praxis, volume 6 issue 2

Contact Info

Product

Resources

About