Prospects of Mobile Search

Search faces (at least) two major challenges. One is to improve efficiency of retrieving relevant content for all digital formats (images, audio, video, 3D shapes, etc). The second is making relevant information retrievable in a range of platforms, particularly in high diffusion ones as mobiles. The two challenges are interrelated but distinct. This report aims at assessing the potential of future Mobile Search. Two broad groups of search-based applications can be identified. The first one is the adaptation and emulation of web search processes and services to the mobile environment. The second one is services exploiting the unique features of the mobile devices and the mobile environments. Examples of these context-aware services include location-based services or interfacing to the internet of things (RFID networks). The report starts by providing an introduction to mobile search. It highlights differences and commonalities with search technologies on other platforms (Chapter 1). Chapter 2 is devoted to the supply side of mobile search markets. It describes mobile markets, presents key figures and gives an outline of main business models and players. Chapter 3 is dedicated to the demand side of the market. It studies users¿ acceptance and demand using the results on a case study in Sweden. Chapter 4 presents emerging trends in technology and markets that could shape mobile search. It is the author's view after discussing with many experts. One input to this discussion was the analysis of on forward-looking scenarios for mobile developed by the authors (Chapter 5). Experts were asked to evaluate these scenarios. Another input was a questionnaire to which 61 experts responded. Drivers, barriers and enablers for mobile search have been synthesised into SWOT analysis. The report concludes with some policy recommendations in view of the likely socio-economic implications of mobile search in Europe.JRC.DG.J.4-Information Societ

Analysis of Search on Clinical Narrative within the EHR

Electronic Health Records (EHRs) are used increasingly in the hospital and outpatient set- tings, and patients are amassing digitized clinical information. On one hand, aggregating all the patient's clinical information can greatly assist health care workers in making sound decisions. On the other hand, it can result in information overload, making it difficult to browse for information within the health record. Considering the time constraints clinicians face, one way to reduce information overload is through a search utility. However, traditional, free-text search engines within the EHR can potentially miss documents that do not contain the query but that are relevant to the clinical user's search. This dissertation aims at addressing this gap by analyzing within-patient search of the EHR and examining various semantic search approaches on clinical narrative. Our work consists of three studies where clinical users' search needs are examined, traditional string-matching is analyzed, and semantic search approaches on clinical narrative are evaluated. The first study applied a mixed method approach in order to provide a better understanding of clinical users' search needs within the EHR. It is comprised of a retrospective log analysis of search log files and a survey that was administered to clinical professionals within our institution. The log analysis attempts to categorize how users of a search system query for information, and the survey tries to understand users' search preferences. This study showed that clinical users were very interested in search functionality within the EHR and that various types of users utilize a search utility differently. Overall, most users searched for specific laboratory tests and diseases within the health record. The last two studies rely on a gold standard, which was developed specifically for this dissertation. The gold standard contained a document collection, a set of queries, and for each document/query pair, a relevance judgment. This gold standard was used to evaluate and compare different search models on clinical narrative. The second study conducted was an error analysis of the traditional, vector-space model search approach. The study examined the false positives and false negatives of this approach and categorized the errors in order to identify gaps that semantic approaches may fill. The last study was a systematic evaluation of five different semantic search approaches. These search methods consisted of distributional semantic approaches and an ontology-based approach. The study identified that a mixed topic modeling and vector-space model approach was the best performing search algorithm on our gold standard. All of these studies lay the foundation for us to gain a deeper understanding of information retrieval methods within the electronic health record. Ultimately, this will allow health care professionals to easily access pertinent patient information, which could result in better health care delivery

Collaboration - changing the global landscape of science: proceedings of 10th International Conference on Webometrics, Informetrics and Scientometrics & 15th COLLNET Meeting 2014, September 3 - 5, 2014, Technische Universität Ilmenau, Germany

The 10th WIS encourages continued investigation into the field of applied scientometrics. The broad focus of the conference is on collaboration and communication in science and technology, science policy, quantitative aspects of science and combination and integration of qualitative and quantitative approaches in study of scientific practices. The conference thus aims to contribute to evidence-based and informed knowledge about scientific research and practices witch in turn may further provide input to institutional, regional, national and international research and innovation policy making