Abstract
To support users in identifying relevant information in the medical web, on the one hand, standards for medical web content were defined to allow certification of quality health information (e.g. the HONcode certification[30]). However, such certificate does not help a user to assess the diverse aspects of web content. Therefore, on the other hand, users need support in finding relevant content by more sophisticated search facilities. Existing web and medical blog search engines (e.g., Medworm [162]) list search results matching query keywords in a flat list. Diversity is—if at all—only considered by presenting different results in the top N positions. In this chapter, a system architecture for a retrieval engine is introduced that allows to exploit (medical) domain specific notions of diversity.
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References
HON. Health on the net foundation. http://www.hon.ch, last accessed: 14.03.2015.
X. Zhou, X. Zhang, and X. Hu. Dragon toolkit: Incorporating auto-learned semantic knowledge into large-scale text retrieval and mining. In Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), October 29–31, 2007, Patras, Greece, 2007.
Jamila Hanan. Medworm. http://www.medworm.com/, last accessed: 14.03.2015.
K. Denecke. An architecture for diversity-aware search for medical web content. Methods of Information in Medicine, 51(6):549–56, 2012.
T. Vanhecke, M. Barnes, J. Zimmerman, and S. Shoichet. PubMed vs. HighWire Press: A head-to-head comparison of two medical literature search engines. Computers in Biology and Medicine, 37(9):1252–1258, September 2007.
P. Daumke, S. Schulz, M.L. Müller, W. Dzeyk, L. Prinzen, E.J. Pacheco, P.S. Cancian, P. Nohama, and K. Marko. Subword-based semantic retrieval of clinical and bibliograpic documents. Methods Inf Med, 49(2):141–47, 2010.
Martin Krallinger and Alfonso Valencia. Text-mining and information-retrieval services for molecular biology. Genome Biology, 6(7):224+, 2005.
T.G. Vit Novacek and S. Handschuh. Coraal towards deep exploitation of textual resources in life sciences. Lecture Notes in Computer Science. Berlin/Heidelberg, 5651/2009:206–215, 2009.
S. Dumais F. Radlinski. Improving personalized web search using result diversification. In SIGIR 2006: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval. New York, USA, pages 691–692, 2006.
D. Carmel A. Anagnostopoulos, A.Z. Broder. Sampling search-engine results. In Proceedings of the 14th international conference on World Wide Web: New York, USA, pages 245–256, 2005.
Chein-Shung Hwang and Show-Fen Lin. Hill climbing for diversity retrieval. Computer Science and Information Engineering, World Congress on, 5:154–158, 2009.
Rakesh Agrawal, Sreenivas Gollapudi, Alan Halverson, and Samuel Ieong. Diversifying search results. In Proceedings of the Second ACM International Conference on Web Search and Data Mining, WSDM ’09, pages 5–14, New York, NY, USA, 2009. ACM.
Sreenivas Gollapudi and Aneesh Sharma. An axiomatic approach for result diversification. In Proceedings of the 18th International Conference on World Wide Web, WWW ’09, pages 381–390, New York, NY, USA, 2009. ACM.
Enrico Minack, Gianluca Demartini, and Wolfgang Nejdl. Current approaches to search result diversification. In Proc. of 1st Intl. Workshop on Living Web, 2009.
Wisam Dakka and Panagiotis G. Ipeirotis. Automatic extraction of useful facet hierarchies from text databases. In Proceedings of the 2008 IEEE 24th International Conference on Data Engineering, ICDE ’08, pages 466–475, Washington, DC, USA, 2008. IEEE Computer Society.
Marti A. Hearst. Clustering versus faceted categories for information exploration. Commun. ACM, 49(4):59–61, April 2006.
J. Diederich and W. T. Balke. Automatically created concept graphs using descriptive keywords in the medical domain. Methods of Information in Medicine, 47(3):241–50, 2008.
SJ. Darmoni, JP. Leroy, F. Baudic, M. Douyere, J. Piot, and B. Thrion. Cismef: a structured health resource guide. Methods of Information in Medicine, 39(1):30–35, 2000.
Angelos Hliaoutakis, Giannis Varelas, Euripides G. M. Petrakis, and Evangelos Milios. Medsearch: A retrieval system for medical information based on semantic similarity. In In Proceedings of ECDL, pages 512–515, 2006.
Gang Luo. Design and evaluation of the imed intelligent medical search engine. In Proceedings of the 2009 IEEE International Conference on Data Engineering, ICDE ’09, pages 1379–1390, Washington, DC, USA, 2009. IEEE Computer Society.
AlchemyAPI. Alchemyapi. http://www.alchemyapi.com/, last accessed: 14.03.2015.
Andrea Esuli and Fabrizio Sebastiani. Sentiwordnet: A publicly available lexical resource for opinion mining. In In Proceedings of the 5th Conference on Language Resources and Evaluation (LREC 2006), pages 417–422, 2006.
Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten. The weka data mining software: An update. SIGKDD Explor. Newsl., 11(1):10–18, November 2009.
Ian H. Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques. The Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann Publishers, San Francisco, CA, 2nd edition, 2005.
H. Mueller, C. Boyer, A. Gaudinat, W. Hersh, and A. Geissbuhler. Analyzing web log files of the health on the net honmedia search engine to define typical image search tasks for image retrieval evaluation. In Stud Health Technol Inform 129 (Pt 2), pages 1319–1323, 2007.
Filip Radlinski and Nick Craswell. Comparing the sensitivity of information retrieval metrics. In Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’10, pages 667–674, New York, NY, USA, 2010. ACM.
Kalervo Järvelin and Jaana Kekäläinen. Ir evaluation methods for retrieving highly relevant documents. In Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’00, pages 41–48, New York, NY, USA, 2000. ACM.
N.H. Shah C. Jonquet and M.A. Musen. The open biomedical annotator. In Summit on Translat Bioinforma, pages 56–60, 2009.
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Denecke, K. (2015). Diversity-Aware Search. In: Health Web Science. Health Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-20582-3_12
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DOI: https://doi.org/10.1007/978-3-319-20582-3_12
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