Identification of re-finding tasks and search difficulty

We address the problem of identifying if users are attempting to re-find information and estimating the level of difficulty of the re-finding task. Identifying re-finding tasks and detecting search difficulties will enable search engines to respond dynamically to the search task being undertaken. To this aim, we conduct user studies and query log analysis to make a better understanding of re-finding tasks and search difficulties. Computing features particularly gathered in our user studies, we generate training sets from query log data, which is used for constructing automatic identification (prediction) models. Using machine learning techniques, our built re-finding identification model, which is the first model at the task level, could significantly outperform the existing query-based identifications. While past research assumes that previous search history of the user is available to the prediction model, we examine if re-finding detection is possible without access to this information. Our evaluation indicates that such detection is possible, but more challenging. We further describe the first predictive model in detecting re-finding difficulty, showing it to be significantly better than existing approaches for detecting general search difficulty. We also analyze important features for both identifications of re-finding and difficulties. Next, we investigate detailed identification of re-finding tasks and difficulties in terms of the type of the vertical document to be re-found. The accuracy of constructed predictive models indicates that re-finding tasks are indeed distinguishable across verticals and in comparison to general search tasks. This illustrates the requirement of adapting existing general search techniques for the re-finding context in terms of presenting vertical-specific results. Despite the overall reduction of accuracy in predictions independent of the original search of the user, it appears that identifying “image re-finding” is less dependent on such past information. Investigating the real-time prediction effectiveness of the models show that predicting ``image'' document re-finding obtains the highest accuracy early in the search. Early predictions would benefit search engines with adaptation of search results during re-finding activities. Furthermore, we study the difficulties in re-finding across verticals given some of the established indications of difficulties in the general web search context. In terms of user effort, re-finding “image” vertical appears to take more effort in terms of number of queries and clicks than other investigated verticals, while re-finding “reference” documents seems to be more time consuming when there is a longer time gap between the re-finding and corresponding original search. Exploring other features suggests that there could be particular difficulty indications for the re-finding context and specific to each vertical. To sum up, this research investigates the issue of effectively supporting users with re-finding search tasks. To this end, we have identified features that allow for more accurate distinction between re-finding and general tasks. This will enable search engines to better adapt search results for the re-finding context and improve the search experience of the users. Moreover, features indicative of similar/different and easy/difficult re-finding tasks can be employed for building balanced test environments, which could address one of the main gaps in the re-finding context

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Temas de actualidad en salud pública

La salud pública es una disciplina importante para la salud en el mundo. Se define como la ciencia y el arte de prevenir las enfermedades, prolongar la vida y promover la salud a través de los esfuerzos organizados y decisiones con conocimiento de la sociedad, las organizaciones (públicas y privadas), las comunidades y los individuos, esta disciplina se ha renovado con la incorporación de múltiples actores, profesiones, áreas de conocimiento, además de ser afectados y promovido por múltiples tecnologías, en particular los de información. Como un campo cambiante del conocimiento, la salud pública requiere la información basada en la evidencia y actualizaciones regulares, más aún en el contexto de un mundo en transición epidemiológica. "Temas actuales en la salud pública", presenta información actualizada sobre varios temas relacionados con las áreas reales de interés en esta ciencia médica creciente y emocionante, con la concepción y la filosofía que estamos trabajando para mejorar la salud de la población, en lugar que el tratamiento de las enfermedades de los pacientes individuales, la toma de decisiones sobre el cuidado de la salud colectiva que se basan en la mejor evidencia disponible, actualizada, válida y pertinente, y, finalmente, en el contexto de los recursos disponibles. La salud pública debe ser una ciencia compleja, ayudando en las decisiones, acciones y cambios en la salud del mundo. En una sociedad globalizada esto se hizo hincapié no sólo en una nación en particular, sino en todo el mundo.Public health is a major health discipline in the world. Defined as the science and art of preventing diseases, prolonging life and promoting health through the organized efforts and informed choices of the society, organizations (public and private), communities and individuals, this discipline has been renewed by the incorporation of multiple actors, professions, knowledge areas, as well as being impacted and promoted by multiple technologies, particularly information ones. As a changing field of knowledge, public health requires evidence-based information and regular updates, even more in the context of a world in epidemiological transition. Health impacts of climate change are currently in the quest of the Millennium Development Goals, and most of them are related to the activities of public health. “Current Topics in Public Health” presents updated information on multiple topics related to actual areas of interest in this growing and exciting medical science, with the conception and philosophy that we are working to improve the health of the population, rather than treating diseases of individual patients; taking decisions about collective health care that are based on the best available, current, valid and relevant evidence; and finally within the context of available resources. Public health should be a complex science helping in the decision, actions and changes in the health of the world. In a globalized society this is emphasized not just in a particular nation but in the whole world