The use of implicit evidence for relevance feedback in web retrieval

In this paper we report on the application of two contrasting types of relevance feedback for web retrieval. We compare two systems; one using explicit relevance feedback (where searchers explicitly have to mark documents relevant) and one using implicit relevance feedback (where the system endeavours to estimate relevance by mining the searcher's interaction). The feedback is used to update the display according to the user's interaction. Our research focuses on the degree to which implicit evidence of document relevance can be substituted for explicit evidence. We examine the two variations in terms of both user opinion and search effectiveness

The liver in amoebic disease

During the past 8 years, 305 cases of amoebic disease have been examined at the Department of Diagnostic Radio-isotopes of the H. F. Verwoerd Hospital, Pretoria. Analysis of the data obtained by means of scintigraphy in 247 of these patients indicates that in vivo scintigraphy of the liver is a valuable method for the investigation of many aspects of the disease. Our observations on the localisation of the abscesses, the relationship between localisation and the frequency of complications, the macroscopical changes in the liver during the disease, the presence of a generalised reaction of the liver parenchyma to amoebae in some cases, and the healing rate of abscesses under different types of treatment, are reported in this article.S. Afr. Med. J., 48, 308 (1974)

Automatically conceptualizing social media analytics data via personas

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Involving users in OPAC interface design: Perspective from a UK study

This is the post-print versoin of the Article. The official published version can be accessed from the link below - Copyright @ 2007 SpringerThe purpose of this study was to determine user suggestions for a typical OPAC (Online Public Library Catalogue) application’s functionality and features. An experiment was undertaken to find out the type of interactions features that users prefer to have in an OPAC. The study revealed that regardless of users’ Information Technology (IT) backgrounds, their functionality expectations of OPACs are the same. However, based on users’ previous experiences with OPACs, their requirements with respect to specific features may change. Users should be involved early in the OPAC development cycle process in order to ensure usable and functional interface

Security guidelines for field research in complex, remote and hazardous places

These guidelines assist researchers in conducting their field-based research or fieldwork in hazardous, remote or complex environments as safely and securely as possible. Fieldwork comes with risks, ranging from the mundane risks of car accidents to more exceptional risks of encountering violence. These risks may affect the security of the researcher and the research outcomes, as well as the security of the respondents, local assistants and interpreters, the home and host organizations, and research sponsors. Taking into account the risk environment should be

"5 Days in August" – How London Local Authorities used Twitter during the 2011 riots

© IFIP International Federation for Information Processing 2012This study examines effects of microblogging communications during emergency events based on the case of the summer 2011 riots in London. During five days in August 2011, parts of London and other major cities in England suffered from extensive public disorders, violence and even loss of human lives. We collected and analysed the tweets posted by the official accounts maintained by 28 London local government authorities. Those authorities used Twitter for a variety of purposes such as preventing rumours, providing official information, promoting legal actions against offenders and organising post-riot community engagement activities. The study shows how the immediacy and communicative power of microblogging can have a significant effect at the response and recovery stages of emergency events

Sentiment Analysis in Twitter for Spanish

The final publication is available at Springer via http://dx.doi.org/ 10.1007/978-3-319-07983-7_27This paper describes a SVM-approach for Sentiment Analysis (SA) in Twitter for Spanish. This task was part of the TASS2013 workshop, which is a framework for SA that is focused on the Spanish language. We describe the approach used, and we present an experimental comparison of the approaches presented by the di erent teams that took part in the competition. We also describe the improvements that were added to our system after our participation in the competition. With these improvements, we obtained an accuracy of 62.88% and 70.25% on the SA test set for 5-level and 3-level tasks respectively. To our knowledge, these results are the best results published until now for the SA tasks of the TASS2013 workshop.This work has been funded by the projects, DIANA (MEC TIN2012-38603-C02-01) and Tímpano (MEC TIN2011-28169-C05-01).Pla Santamaría, F.; Hurtado Oliver, LF. (2014). Sentiment Analysis in Twitter for Spanish. En Natural Language Processing and Information Systems. Springer Lecture Notes in Computer Science Volume 8455 2014. 208-213. https://doi.org/10.1007/978-3-319-07983-7_27S208213Barbosa, L., Feng, J.: Robust sentiment detection on Twitter from biased and noisy data. In: Proceedings of the 23rd International Conference on Computational Linguistics: Posters, Association for Computational Linguistics, pp. 36–44 (2010)Jansen, B.J., Zhang, M., Sobel, K., Chowdury, A.: Twitter power: Tweets as electronic word of mouth. Journal of the American Society for Information Science and Technology 60(11), 2169–2188 (2009)Liu, B., Hu, M., Cheng, J.: Opinion observer: Analyzing and comparing opinions on the web. In: Proceedings of the 14th International Conference on World Wide Web, WWW 2005, pp. 342–351. ACM, New York (2005)Martínez-Cámara, E., Martín-Valdivia, M.T., Ureña-López, L.A., Montejo-Raéz, A.: Sentiment analysis in twitter. Natural Language Engineering 1(1), 1–28 (2012)O’Connor, B., Krieger, M., Ahn, D.: Tweetmotif: Exploratory search and topic summarization for twitter. In: Cohen, W.W., Gosling, S. (eds.) Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM 2010, Washington, DC, USA, May 23-26, The AAAI Press (2010)Padró, L., Stanilovsky, E.: Freeling 3.0: Towards wider multilinguality. In: Proceedings of the Language Resources and Evaluation Conference (LREC 2012). ELRA, Istanbul (2012)Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? sentiment classification using machine learning techniques. In: Proceedings of EMNLP, pp. 79–86 (2002)Perez-Rosas, V., Banea, C., Mihalcea, R.: Learning sentiment lexicons in spanish. In: Chair, N.C.C., Choukri, K., Declerck, T., Doǧan, M.U., Maegaard, B., Mariani, J., Odijk, J., Piperidis, S. (eds.) Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC 2012). European Language Resources Association (ELRA), Istanbul (2012)Pla, F., Hurtado, L.F.: Análisis de sentimientos en twitter. In: Proceedings of the TASS workshop at SEPLN 2013, IV Congreso Español de Informática (2013)Saralegi, X., San Vicente, I.: Elhuyar at tass 2013. In: Proceedings of the TASS workshop at SEPLN 2013, IV Congreso Español de Informática (2013)Schölkopf, B., Smola, A.J., Williamson, R.C., Bartlett, P.L.: New support vector algorithms. Neural Comput. 12(5), 1207–1245 (2000)Turney, P.D.: Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: ACL, pp. 417–424 (2002)Villena-Román, J., García-Morera, J.: Workshop on sentiment analysis at sepln 2013: An over view. In: Proceedings of the TASS Workshop at SEPLN 2013, IV Congreso Español de Informática (2013)Vinodhini, G., Chandrasekaran, R.: Sentiment analysis and opinion mining: A survey. International Journal 2(6) (2012)Wilson, T., Hoffmann, P., Somasundaran, S., Kessler, J., Wiebe, J., Choi, Y., Cardie, C., Riloff, E., Patwardhan, S.: Opinionfinder: A system for subjectivity analysis. In: Proceedings of HLT/EMNLP on Interactive Demonstrations, Association for Computational Linguistics, pp. 34–35 (2005)Wilson, T., Kozareva, Z., Nakov, P., Rosenthal, S., Stoyanov, V., Ritter, A.: Semeval-2013 task 2: Sentiment analysis in twitter. In: Proceedings of the International Workshop on Semantic Evaluation, SemEval, vol. 13 (2013