Abstract
RSS, a popular method of syndicating frequently updated on-line content, allows data to be stored in a semi-structured, XML-based format. Much work has been carried out applying data mining techniques to RSS, but in this paper we propose the visualRSS (vRSS) application as a platform to mine and visualise data trends in RSS feeds, by tracking changes in keyword frequencies as a source of social data. Core components of vRSS’s architecture to manipulate RSS feeds are described. We also present the results of vRSS’s initial experimental usage involving 36 students in late 2011, concerning our research into preferences of mining types and visualisations.
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Bray, T., Paoli, J., Sperberg-McQueen, C., Maler, E., Yeargeau, F.: Extensible markup language (xml) 1.0, 3rd edn. W3C Recommendation (2004), http://www.w3.org/TR/2004/REC-xml-20040204/
O’Shea, M., Levene, M.: Mining and visualising information from RSS feeds: a case study. IJWIS 7(2), 105–129 (2011)
Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann Series in Data Management Systems. Morgan Kaufmann (2005)
Ohlhorst, F.: Tools to help analyze mountains of social data (2011), http://www.informationweek.com/thebrainyard/news/marketing/231002135/
Dumbill, E.: What is big data? An introduction to the big data landscape (2012), http://radar.oreilly.com/2012/01/what-is-big-data.html
Thelwall, M., Prabowo, R., Fairclough, R.: Are raw RSS feeds suitable for broad issue scanning? a science concern case study. J. Am. Soc. Inf. Sci. Technol. 57(12), 1644–1654 (2006)
Teng, Z., Liu, Y., Ren, F.: Create special domain news collections through summarization and classification. IEEJ Transactions on Electrical and Electronic Engineering 5, 56–61 (2010)
Getahun, F., Tekli, J., Chbeir, R., Viviani, M., Yetongnon, K.: Relating RSS News/Items. In: Gaedke, M., Grossniklaus, M., Díaz, O. (eds.) ICWE 2009. LNCS, vol. 5648, pp. 442–452. Springer, Heidelberg (2009)
Hu, C.L., Chou, C.K.: RSS watchdog: an instant event monitor on real online news streams. In: CIKM 2009: Proceeding of the 18th ACM Conference on Information and Knowledge Management, pp. 2097–2098. ACM, New York (2009)
Bossa, S., Fiumara, G., Provetti, A.: A lightweight architecture for RSS polling of arbitrary web sources. In: WOA (2006)
Roesler, R.: Relational RSS clustering techniques (2010), http://www.stanford.edu/class/cs229/proj2009/Roesler.pdf
Hsu, L.-F.: Mining on Terms Extraction from Web News. In: Pan, J.-S., Chen, S.-M., Nguyen, N.T. (eds.) ICCCI 2010, Part I. LNCS, vol. 6421, pp. 188–194. Springer, Heidelberg (2010)
Kittiphattanabawon, N., Theeramunkong, T.: Relation Discovery from Thai News Articles Using Association Rule Mining. In: Chen, H., Yang, C.C., Chau, M., Li, S.-H. (eds.) PAISI 2009. LNCS, vol. 5477, pp. 118–129. Springer, Heidelberg (2009)
Banerjee, S., Ramanathan, K., Gupta, A.: Clustering short texts using wikipedia. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2007, pp. 787–788. ACM, New York (2007)
Phan, X.H., Nguyen, L.M., Horiguchi, S.: Learning to classify short and sparse text & web with hidden topics from large-scale data collections. In: Proceeding of the 17th International Conference on World Wide Web, pp. 91–100. ACM, New York (2008)
Šilić, A., Bašić, B.D.: Visualization of Text Streams: A Survey. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds.) KES 2010, Part II. LNCS, vol. 6277, pp. 31–43. Springer, Heidelberg (2010)
Wanner, F., Rohrdantz, C., Mansmann, F., Oelke, D., Keim, D.A.: Visual sentiment analysis of RSS news feeds featuring the US presidential election in 2008. In: IUI 2009 Workshop on Visual Interfaces to the Social and the Semantic Web, VISSW (2009), Online Proceedings, http://ceur-ws.org/Vol-443/paper7.pdf
Viégas, F.B., Wattenberg, M., Heer, J., Agrawala, M.: Social data analysis workshop. In: CHI 2008: CHI 2008: Extended Abstracts on Human Factors in Computing Systems, pp. 3977–3980. ACM, New York (2008)
10x10 (2012), http://www.tenbyten.org/
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O’Shea, M., Levene, M. (2012). visualRSS: A Platform to Mine and Visualise Social Data from RSS Feeds. In: Grossniklaus, M., Wimmer, M. (eds) Current Trends in Web Engineering. ICWE 2012. Lecture Notes in Computer Science, vol 7703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35623-0_13
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DOI: https://doi.org/10.1007/978-3-642-35623-0_13
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