Web2Touch 2016: Evolution and security of collaborative web knowledge

This report introduces the Web2Touch 2016, a Track at the 25th IEEE WETICE Conference. This track involves works from collaborative web knowledge research community and related themes. Web2Touch 2016 explores the state-of-the-art on users' practical experiences, as well as trends and research topics paving the way for future collaborative approaches to knowledge management. Papers come from areas such as computational analysis, management of contextual information, support to personalized information management, collaborative knowledge production, consistency, knowledge engineering and security modeling for multiple knowledge sources. The overall focus is on determining how to route, organize, and present contextual and meaningful information and services to facilitate collaboration

Review of Intent Diversity in Information Retrieval : Approaches, Models and Trends

The fast increasing volume of information databases made some difficulties for a user to find the information that they need. Its important for researchers to find the best method for challenging this problem. user intention detection can be used to increase the relevancies of information delivered from the information retrieval system. This research used a systematic mapping process to identify what area, approaches, and models that mostly used to detect user intention in information retrieval in four years later. the result of this research identified that item-based approach is still the most approach researched by researchers to identify intent diversity in information retrieval. The used of item-based approach still increasing from 2015 until 2017. 34% paper used topic models in their research. It means that Topic models still the necessary models explored by the researchers in this study

From a simple EHR to the market lead: what technologies to add

Electronic health records (EHRs) can store, capture, and present patient data in an organized way that improves physicians’ workflow and patient care. This makes EHRs key to addressing many of today’s health care challenges. An interdisciplinary review and qualitative study of artificial intelligence, machine learning, natural language processing, and real-time location services in health care was conducted. The results show that in an industry where digitization is key, several recommendations can be made to leverage these technologies in ways that can improve current systems and help EHR vendors become the market lead

Intention-based Information Retrieval Of Electronic Health Records

The large volume of information stored in electronical health records is very valuable in the medical field, e.g., for clinical research and administrative purposes. However, health care professionals still face difficulties to recover and select relevant data. Although literature has investigated the influence of lexical, syntactical and semantic parameters in information retrieval techniques, few studies explore intentions as explicit users' actions in information recovery. This article studies means of considering intentions in search engines. We define a method with an original algorithm to properly rank search results from a set of electronical health records. This investigation relies on well-established theories to categorize several types of intentions. The proposed technique is based on knowledge representation models for annotating meanings and intentions in medical records. Achieved results are illustrated in scenarios based on real medical cases.21722225th IEEE International Conference on Enabling Technologies - Infrastructure for Collaborative Enterprises (WETICE)JUN 13-15, 2016Paris, FRANC