%0 %0 Journal Article %A Atzmueller, Martin; Becker, Martin; Kibanov, Mark; Scholz, Christoph; Doerfel, Stephan; Hotho, Andreas; Macek, Bjoern-Elmar; Mitzlaff, Folke; Mueller, Juergen & Stumme, Gerd %D 2014 %T Ubicon and its Applications for Ubiquitous Social Computing %E %B New Review of Hypermedia and Multimedia %C %I %V 20 %6 %N 1 %P 53--77 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F atzmueller2014ubicon %K 2014, analytics, mining, myown, social, ubicon, ubiquitous %X The combination of ubiquitous and social computing is an emerging research area which integrates different but complementary methods, techniques and tools. In this paper, we focus on the Ubicon platform, its applications, and a large spectrum of analysis results. Ubicon provides an extensible framework for building and hosting applications targeting both ubiquitous and social environments. We summarize the architecture and exemplify its implementation using four real-world applications built on top of Ubicon. In addition, we discuss several scientific experiments in the context of these applications in order to give a better picture of the potential of the framework, and discuss analysis results using several real-world data sets collected utilizing Ubicon. %Z %U http://www.tandfonline.com/doi/abs/10.1080/13614568.2013.873488 %+ %^ %0 %0 Conference Proceedings %A %D 2014 %T Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, DMNLP@PKDD/ECML 2014, Nancy, France, September 15, 2014 %E Cellier, Peggy; Charnois, Thierry; Hotho, Andreas; Matwin, Stan; Moens, Marie-,Francine & Toussaint, Yannick %B %C %I CEUR-WS.org %V 1202 %6 %N %P %& %Y %S {CEUR} Workshop Proceedings %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 proceedings %4 %# %$ %F cellier2014proceedings %K 2014, data, mining, myown, nlp, workshop %X %Z %U http://ceur-ws.org/Vol-1202 %+ %^ %0 %0 Book %A %D 2012 %T Modeling and Mining Ubiquitous Social Media %E Atzmueller, Martin; Chin, Alvin; Helic, Denis & Hotho, Andreas %B Lecture Notes in Computer Science %C Heidelberg, Germany %I Springer Verlag %V 7472 %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 book %4 %# %$ %F ACHH:12 %K 2012, everyaware, media, mining, modeling, myown, social, ubiquitous %X %Z %U http://www.springer.com/computer/ai/book/978-3-642-33683-6 %+ %^ %0 %0 Book %A %D 2012 %T Proceedings of the Third International Workshop on Mining Ubiquitous and Social Environments (MUSE 2012) %E Atzmueller, Martin & Hotho, Andreas %B %C Bristol, UK %I Workshop Notes %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 book %4 %# %$ %F AH:12 %K 2012, mining, muse, myown %X %Z %U http://www.kde.cs.uni-kassel.de/ws/muse2012/proceedings.pdf %+ %^ %0 %0 Generic %A Han, Jiawei; Kamber, Micheline & Pei, Jian %D 2012 %T Data mining concepts and techniques, third edition %E %B %C %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 Data Mining: Concepts and Techniques (Morgan Kaufmann Series in Data Management Systems): Amazon.de: Jiawei Han, Micheline Kamber, Jian Pei: Englische Bücher %3 %4 %# %$ %F han2012mining %K data, mining, tobuy %X %Z %U http://www.amazon.de/Data-Mining-Concepts-Techniques-Management/dp/0123814790/ref=tmm_hrd_title_0?ie=UTF8&qid=1366039033&sr=1-1 %+ %^ %0 %0 Book %A North, Matthew %D 2012 %T Data mining for the masses %E %B %C %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ 9780615684376 0615684378 %( %) %* %L %M %1 %2 Data Mining for the Masses: Amazon.de: Dr. Matthew A North: Englische Bücher %3 book %4 %# %$ %F north2012mining %K data, mining, tobuy %X %Z %U http://www.amazon.de/Data-Mining-Masses-Matthew-North/dp/0615684378/ref=sr_1_1?s=books-intl-de&ie=UTF8&qid=1366038800&sr=1-1&keywords=rapidminer %+ %^ %0 %0 Book %A %D 2011 %T Proceedings of the 2011 International Workshop on Mining Ubiquitous and Social Environments (MUSE 2011) %E Atzmueller, Martin & Hotho, Andreas %B %C Athens, Greece %I ECML/PKDD 2011 %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 book %4 %# %$ %F AH:11 %K 2011, mining, muse, myown %X %Z %U %+ %^ %0 %0 Conference Proceedings %A Atzmueller, Martin; Benz, Dominik; Hotho, Andreas & Stumme, Gerd %D 2011 %T Towards Mining Semantic Maturity in Social Bookmarking Systems %E Passant, Alexandre; Fernández, Sergio; Breslin, John & Bojārs, Uldis %B Proceedings of the 4th international workshop on Social Data on the Web (SDoW2011) %C %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F atzmueller2011towards %K 2011, bookmarking, mining, myown, pattern, semantic, social %X %Z %U http://www.kde.cs.uni-kassel.de/pub/pdf/atzmueller2011towards.pdf %+ %^ %0 %0 Conference Proceedings %A Bloehdorn, Stephan; Blohm, Sebastian; Cimiano, Philipp; Giesbrecht, Eugenie; Hotho, Andreas; Lösch, Uta; Mädche, Alexander; Mönch, Eddie; Sorg, Philipp; Staab, Steffen & Völker, Johanna %D 2011 %T Combining Data-Driven and Semantic Approaches for Text Mining. %E Fensel, Dieter %B Foundations for the Web of Information and Services %C %I Springer %V %6 %N %P 115-142 %& %Y %S %7 %8 %9 %? %! %Z %@ 978-3-642-19796-3 %( %) %* %L %M %1 %2 %3 inproceedings %4 conf/birthday/2011studer %# %$ %F conf/birthday/BloehdornBCGHLMMSSV11 %K 2011, data, mining, myown, semantic, text %X %Z %U http://dblp.uni-trier.de/db/conf/birthday/studer2011.html#BloehdornBCGHLMMSSV11 %+ %^ %0 %0 Book %A Han, Jiawei & Kamber, Micheline %D 2011 %T Data mining : concepts and techniques %E %B %C Amsterdam [u.a.] %I Elsevier/Morgan Kaufmann %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ 9780123814791 0123814790 %( %) %* %L %M %1 %2 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems): Amazon.de: Ian H. Witten, Eibe Frank, Mark A. Hall: Englische Bücher %3 book %4 %# %$ %F han2011mining %K data, mining, tobuy, weka %X %Z %U http://www.amazon.de/Data-Mining-Practical-Techniques-Management/dp/0123748569/ref=sr_1_2?ie=UTF8&qid=1366038862&sr=8-2&keywords=Data+mining %+ %^ %0 %0 Conference Proceedings %A Hotho, Andreas & Stumme, Gerd %D 2011 %T From Semantic Web Mining to Social and Ubiquitous Mining - A Subjective View on Past, Current, and Future Research. %E Fensel, Dieter %B Foundations for the Web of Information and Services %C %I Springer %V %6 %N %P 143-153 %& %Y %S %7 %8 %9 %? %! %Z %@ 978-3-642-19796-3 %( %) %* %L %M %1 %2 %3 inproceedings %4 conf/birthday/2011studer %# %$ %F conf/birthday/HothoS11 %K 2011, mining, myown, social, ubiquitous, web %X %Z %U http://dblp.uni-trier.de/db/conf/birthday/studer2011.html#HothoS11 %+ %^ %0 %0 Conference Proceedings %A Mitzlaff, Folke; Atzmueller, Martin; Benz, Dominik; Hotho, Andreas & Stumme, Gerd %D 2011 %T Community Assessment using Evidence Networks %E %B Analysis of Social Media and Ubiquitous Data %C %I %V 6904 %6 %N %P %& %Y %S LNAI %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F mitzlaff2011community %K 2011, community, evaluation, knowledge, mining, myown %X %Z %U %+ %^ %0 %0 Conference Proceedings %A Mitzlaff, Folke; Atzmueller, Martin; Stumme, Gerd & Hotho, Andreas %D 2011 %T On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission) %E %B Proc. LWA 2013 (KDML Special Track) %C Bamberg, Germany %I University of Bamberg %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 %# %$ %F MASH:13b %K 2013, mining, myown, social, ubiquitous %X %Z %U %+ %^ %0 %0 Generic %A Rubin, Timothy N.; Chambers, America; Smyth, Padhraic & Steyvers, Mark %D 2011 %T Statistical Topic Models for Multi-Label Document Classification %E %B %C %I %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 Statistical Topic Models for Multi-Label Document Classification %3 misc %4 %# %$ %F Rubin2011 %K mining, model, text, tm, topic, toread %X Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches is that performance rapidly drops off as the total number of labels and the number of labels per document increase. This problem is amplified when the label frequencies exhibit the type of highly skewed distributions that are often observed in real-world datasets. In this paper we investigate a class of generative statistical topic models for multi-label documents that associate individual word tokens with different labels. We investigate the advantages of this approach relative to discriminative models, particularly with respect to classification problems involving large numbers of relatively rare labels. We compare the performance of generative and discriminative approaches on document labeling tasks ranging from datasets with several thousand labels to datasets with tens of labels. The experimental results indicate that generative models can achieve competitive multi-label classification performance compared to discriminative methods, and have advantages for datasets with many labels and skewed label frequencies. %Z cite arxiv:1107.2462 %U http://arxiv.org/abs/1107.2462 %+ %^ %0 %0 Journal Article %A Hotho, Andreas; Ulslev Pedersen,, Rasmus & Wurst, Michael %D 2010 %T Ubiquitous Data %E %B Lecture Notes in Computer Science %C %I Springer %V %6 %N 6202 %P 61--74 %& %Y %S %7 %8 %9 %? %! %Z %@ 0302-9743 %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F hotho2010ubiquitous %K 2010, data, dm, mining, myown, social, ubiquitous %X %Z %U http://rd.springer.com/content/pdf/10.1007%2F978-3-642-16392-0_4.pdf %+ %^ %0 %0 Conference Proceedings %A Yassine, Mohamed & Hajj, Hazem %D 2010 %T A Framework for Emotion Mining from Text in Online Social Networks. %E Fan, Wei; Hsu, Wynne; Webb, Geoffrey I.; Liu, Bing; Zhang, Chengqi; Gunopulos, Dimitrios & Wu, Xindong %B ICDM Workshops %C %I IEEE Computer Society %V %6 %N %P 1136-1142 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 %3 inproceedings %4 conf/icdm/2010w %# %$ %F conf/icdm/YassineH10 %K emotion, everyaware, mining, text, toread %X %Z %U http://dblp.uni-trier.de/db/conf/icdm/icdmw2010.html#YassineH10 %+ %^ %0 %0 Book %A Srivastava, Asho & Sahami, Mehran. %D 2009 %T Text mining : classification, clustering, and applications %E %B %C Boca Raton, FL %I CRC Press %V %6 %N %P %& %Y %S %7 %8 %9 %? %! %Z %@ 9781420059403 1420059408 %( %) %* %L %M %1 %2 CRC Press Online - Book: Text Mining %3 book %4 %# %$ %F srivastava2009mining %K mining, text, toread %X Giving a broad perspective of the field from numerous vantage points, 'Text Mining' focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify text documents and applies these methods in a variety of areas. %Z %U http://www.worldcat.org/search?qt=worldcat_org_all&q=9781420059403 %+ %^ %0 %0 Journal Article %A Crane, Gregory %D 2006 %T What Do You Do with a Million Books? %E %B D-Lib Magazine %C %I %V 12 %6 %N 3 %P %& %Y %S %7 %8 March %9 %? %! %Z %@ 1082-9873 %( %) %* %L %M %1 %2 %3 article %4 %# %$ %F march06crane %K Book, Mining, Text, google, tm, toread %X %Z %U http://www.dlib.org/dlib/march06/crane/03crane.html %+ %^ %0 %0 Journal Article %A Berkhin, Pavel %D 2005 %T A survey on pagerank computing %E %B Internet Mathematics %C %I %V 2 %6 %N %P 73--120 %& %Y %S %7 %8 %9 %? %! %Z %@ %( %) %* %L %M %1 %2 A survey on pagerank computing %3 article %4 %# %$ %F Berkhin05asurvey %K data, mining, pagerank, survey %X Abstract. This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much more complex challenge. Recently, significant effort has been invested in building sets of personalized PageRank vectors. PageRank is also used in many diverse applications other than ranking. We are interested in the theoretical foundations of the PageRank formulation, in the acceleration of PageRank computing, in the effects of particular aspects of web graph structure on the optimal organization of computations, and in PageRank stability. We also review alternative models that lead to authority indices similar to PageRank and the role of such indices in applications other than web search. We also discuss linkbased search personalization and outline some aspects of PageRank infrastructure from associated measures of convergence to link preprocessing. 1. %Z %U http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.2294 %+ %^ %0 %0 Book Section %A Fayyad, Usama M.; Piatetsky-Shapiro, Gregory & Smyth, Padhraic %D 1996 %T Advances in knowledge discovery and data mining %E Fayyad, Usama M.; Piatetsky-Shapiro, Gregory; Smyth, Padhraic & Uthurusamy, Ramasamy %B %C Menlo Park, CA, USA %I American Association for Artificial Intelligence %V %6 %N %P 1--34 %& From data mining to knowledge discovery: an overview %Y %S %7 %8 %9 %? %! %Z %@ 0-262-56097-6 %( %) %* %L %M %1 %2 From data mining to knowledge discovery %3 incollection %4 %# %$ %F Fayyad:1996:DMK:257938.257942 %K data, definition, discovery, knowledge, mining %X %Z %U http://portal.acm.org/citation.cfm?id=257938.257942 %+ %^