This paper reports on the 2nd ShARe/CLEFeHealth evaluation lab which continues our evaluation resource building activities for the medical domain. In this lab we focus on patients' information needs as opposed to the more common campaign focus of the specialised information needs of physicians and other healthcare workers. The usage scenario of the lab is… (More)
This paper presents the results of task 3 of the ShARe/CLEF eHealth Evaluation Lab 2014. This evaluation lab focuses on improving access to medical information on the web. The task objective was to investigate the effect of using additional information such as a related discharge summary and external resources such as medical ontologies on the effectiveness… (More)
This paper reports on the 3rd CLEFeHealth evaluation lab, which continues our evaluation resource building activities for the medical domain. In this edition of the lab, we focus on easing patients and nurses in authoring, understanding, and accessing eHealth information. The 2015 CLEFeHealth evaluation lab was structured into two tasks, fo-cusing on… (More)
This paper details methods, results and analysis of the CLEF 2015 eHealth Evaluation Lab, Task 2. This task investigates the effectiveness of web search engines in providing access to medical information with the aim of fostering advances in the development of these technologies. The problem considered in this year's task was to retrieve web pages to… (More)
This paper details the collection, systems and evaluation methods used in the IR Task of the CLEF 2016 eHealth Evaluation Lab. This task investigates the e↵ectiveness of web search engines in providing access to medical information for common people that have no or little medical knowledge. The task aims to foster advances in the development of search… (More)
—Capacity management of a hosting infrastructure has traditionally focused only on performance goals. However, the quality of service provided to the hosted applications, and ultimately the revenues achieved by the provider, depend also on other aspects, such as security and energy constraints. This paper extends our self-adaptive SLA-driven capacity… (More)
This paper describes the efforts of Vienna University of Technology (TUW) in the MediaEval 2014 Retrieving Diverse Social Images challenge. Our approach consisted of 3 steps: (1) a pre-filtering based on Machine Learning, (2) a re-ranking based on Word2Vec, and (3) a clustering part based on an ensemble of clusters. Our best run reached a F@20 of 0.564.
This paper investigates the effect that text pre-processing approaches have on the estimation of the readability of web pages. Readability has been highlighted as an important aspect of web search result personalisation in previous work. The most widely used text readability measures rely on surface level characteristics of text, such as the length of words… (More)