@electronic{www.coursera.org, title = {Mining Massive Datasets - Stanford University | Coursera}, url = {https://www.coursera.org/course/mmds}, biburl = {https://puma.uni-kassel.de/url/a83f03d8d818f23ff6f40f46a8f18f98/hotho}, keywords = {book buch data dataset massive mining}, added-at = {2015-09-15T14:10:45.000+0200}, description = {Take free online classes from 120+ top universities and educational organizations. We partner with schools like Stanford, Yale, Princeton, and others to offer courses in dozens of topics, from computer science to teaching and beyond. Whether you are pursuing a passion or looking to advance your career, Coursera provides open, free education for everyone.}, interhash = {a83f03d8d818f23ff6f40f46a8f18f98}, intrahash = {a83f03d8d818f23ff6f40f46a8f18f98} } @electronic{dmnlp.loria.fr, title = {DMNLP 2014 Worshop | Main / The DMNLP Workshop}, url = {http://dmnlp.loria.fr/}, biburl = {https://puma.uni-kassel.de/url/6bdb1973bb8a0c0760362f617517202a/hotho}, keywords = {2014 data dmnlp mining myown nlp workshop}, added-at = {2014-10-29T12:09:16.000+0100}, description = {}, interhash = {6bdb1973bb8a0c0760362f617517202a}, intrahash = {6bdb1973bb8a0c0760362f617517202a} } @electronic{www.stm-assoc.org, title = {Microsoft Word - 2013_11_11_Text_and_Data_Mining_Declaration.doc - 2013_11_11_Text_and_Data_Mining_Declaration.pdf}, url = {http://www.stm-assoc.org/2013_11_11_Text_and_Data_Mining_Declaration.pdf}, biburl = {https://puma.uni-kassel.de/url/332b7f5b1b6633c94bef77be3ccadfa5/hotho}, keywords = {access data dataset journal mining paper sota text}, added-at = {2013-11-27T08:54:41.000+0100}, description = {}, interhash = {332b7f5b1b6633c94bef77be3ccadfa5}, intrahash = {332b7f5b1b6633c94bef77be3ccadfa5} } @electronic{www.asis.org, title = {Methodological Approach in Discovering User Search Patterns through Web Log Analysis}, url = {http://www.asis.org/Bulletin/Oct-00/janses___spink.html}, biburl = {https://puma.uni-kassel.de/url/2a3bc2437a868a19b25d26e7f7bacaf8/stephandoerfel}, keywords = {methodology mining weblog}, added-at = {2013-03-30T15:03:16.000+0100}, description = {}, interhash = {2a3bc2437a868a19b25d26e7f7bacaf8}, intrahash = {2a3bc2437a868a19b25d26e7f7bacaf8} } @electronic{wsdm2012.org, title = {Web Search and Data Mining (WSDM) 2012}, url = {http://wsdm2012.org/}, biburl = {https://puma.uni-kassel.de/url/219bf5d476dc619cf748a3cceed62860/hotho}, keywords = {2012 conference data dm member mining pc}, added-at = {2013-02-26T14:01:01.000+0100}, description = {}, interhash = {219bf5d476dc619cf748a3cceed62860}, intrahash = {219bf5d476dc619cf748a3cceed62860} } @electronic{sourceforge.net, title = {RapidMiner -- Data Mining, ETL, OLAP, BI - Browse Files at SourceForge.net}, url = {http://sourceforge.net/projects/rapidminer/files/}, biburl = {https://puma.uni-kassel.de/url/695c10c41226237562996a7364478bfa/stephandoerfel}, keywords = {data download kdd mining rapidminer}, added-at = {2012-10-23T18:31:12.000+0200}, description = {No 1 in Business Analytics: Data Mining, Predictive Analytics, ETL, Reporting, Dashboards in One Tool. 1000+ methods: data mining, business …}, interhash = {695c10c41226237562996a7364478bfa}, intrahash = {695c10c41226237562996a7364478bfa} } @electronic{es.scribd.com, title = {MIME (Making Interactive Mining Easy)}, url = {http://es.scribd.com/doc/86055727/MIME-Making-Interactive-Mining-Easy}, biburl = {https://puma.uni-kassel.de/url/39e85e9ace6f9e155ec33fb45628478c/stephandoerfel}, keywords = {apriori cartification icfca interacitve itemset mine mining}, added-at = {2012-05-10T10:04:40.000+0200}, description = {}, interhash = {39e85e9ace6f9e155ec33fb45628478c}, intrahash = {39e85e9ace6f9e155ec33fb45628478c} } @electronic{www.kde.cs.uni-kassel.de, title = {3rd International Workshop on Mining Ubiquitous and Social Environments - @ ECML/PKDD 2012}, url = {http://www.kde.cs.uni-kassel.de/ws/muse2012/}, biburl = {https://puma.uni-kassel.de/url/7a5d54bf887baf2c727caa1a746c90d1/hotho}, keywords = {2012 chair ecml mining muse myown pkdd ubiquitous workshop}, added-at = {2012-04-18T14:42:43.000+0200}, description = {}, interhash = {7a5d54bf887baf2c727caa1a746c90d1}, intrahash = {7a5d54bf887baf2c727caa1a746c90d1} } @electronic{wsdm2013.org, title = {Home}, url = {http://wsdm2013.org/}, biburl = {https://puma.uni-kassel.de/url/e19d51609983b68ab44ffc0e54572770/hotho}, keywords = {2013 conference data dm mining pc}, added-at = {2012-04-05T17:21:41.000+0200}, description = {}, interhash = {e19d51609983b68ab44ffc0e54572770}, intrahash = {e19d51609983b68ab44ffc0e54572770} } @electronic{www.borgelt.net, title = {Christian Borgelt's Web Pages}, url = {http://www.borgelt.net/apriori.html}, biburl = {https://puma.uni-kassel.de/url/c3181ed91f002a0117197d7bcbb03d02/stephandoerfel}, keywords = {algorithm apriori borgelts christian data mining}, added-at = {2012-02-24T15:11:03.000+0100}, description = {}, interhash = {c3181ed91f002a0117197d7bcbb03d02}, intrahash = {c3181ed91f002a0117197d7bcbb03d02} } @electronic{reality.media.mit.edu, title = {MIT Media Lab: Reality Mining}, url = {http://reality.media.mit.edu/}, biburl = {https://puma.uni-kassel.de/url/365294ebae4828f93aca9d32ab116908/hotho}, keywords = {data dm everyaware lab media mining reality traces dataset}, added-at = {2011-09-30T08:49:38.000+0200}, description = {}, interhash = {365294ebae4828f93aca9d32ab116908}, intrahash = {365294ebae4828f93aca9d32ab116908} } @electronic{www.cs.cmu.edu, title = {Mining Billion-node Graphs: Patterns and Tools}, url = {http://www.cs.cmu.edu/~christos/TALKS/11-LinkedIn/FOILS/faloutsos_linkedin_2011.pdf}, biburl = {https://puma.uni-kassel.de/url/1f1029ec1bad0fd9e70fd7778326fa87/hotho}, keywords = {graph linkedin mining tools toread}, added-at = {2011-06-22T10:38:14.000+0200}, description = {}, interhash = {1f1029ec1bad0fd9e70fd7778326fa87}, intrahash = {1f1029ec1bad0fd9e70fd7778326fa87} } @electronic{compbio.cs.uic.edu, title = {AMAI: Local Pattern Mining Special Issue cfp}, url = {http://compbio.cs.uic.edu/AMAI-LocalPatterns/}, biburl = {https://puma.uni-kassel.de/url/7b610ba4463ea992c76df73db46a9f5e/stephandoerfel}, keywords = {ai amai community descriptive graph intelligence issue journal local mining pattern special}, added-at = {2011-06-21T10:13:50.000+0200}, description = {}, interhash = {7b610ba4463ea992c76df73db46a9f5e}, intrahash = {7b610ba4463ea992c76df73db46a9f5e} } @electronic{www.kde.cs.uni-kassel.de, title = {2nd International Workshop on Mining Ubiquitous and Social Environments - @ ECML/PKDD 2011}, url = {http://www.kde.cs.uni-kassel.de/ws/muse2011/}, biburl = {https://puma.uni-kassel.de/url/ac1075e0a6219d6ec0e7dd5ba0c65d00/hotho}, keywords = {2011 ecml mining myown pkdd social ubiquitous workshop}, added-at = {2011-05-24T09:47:28.000+0200}, description = {}, interhash = {ac1075e0a6219d6ec0e7dd5ba0c65d00}, intrahash = {ac1075e0a6219d6ec0e7dd5ba0c65d00} } @electronic{tunedit.org, title = {TunedIT - Data mining & machine learning data sets, algorithms, challenges}, url = {http://tunedit.org/}, biburl = {https://puma.uni-kassel.de/url/94fa145e5cfdfa41c41ca7d954f43d23/hotho}, keywords = {challenge data learning machine mining}, added-at = {2011-05-18T13:11:07.000+0200}, description = {Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning}, interhash = {94fa145e5cfdfa41c41ca7d954f43d23}, intrahash = {94fa145e5cfdfa41c41ca7d954f43d23} } @electronic{www.sigkdd.org, title = {KDD 2011: 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining}, url = {http://www.sigkdd.org/kdd2011/}, biburl = {https://puma.uni-kassel.de/url/798e861435532fcec0a1ef2aad01ec8f/hotho}, keywords = {2011 conference data dm kdd mining pc}, added-at = {2011-05-02T19:30:36.000+0200}, description = {}, interhash = {798e861435532fcec0a1ef2aad01ec8f}, intrahash = {798e861435532fcec0a1ef2aad01ec8f} } @electronic{www.cikm2011.org, title = {CIKM 2011}, url = {http://www.cikm2011.org/}, biburl = {https://puma.uni-kassel.de/url/ffaf837e27c0696122e6b2028fa1556d/hotho}, keywords = {2011 conference data dm knowledge management mining pc}, added-at = {2011-04-25T12:21:15.000+0200}, description = {}, interhash = {ffaf837e27c0696122e6b2028fa1556d}, intrahash = {ffaf837e27c0696122e6b2028fa1556d} } @electronic{www.ecmlpkdd2011.org, title = {ECML-PKDD 2011 in Athens, Greece}, url = {http://www.ecmlpkdd2011.org/}, biburl = {https://puma.uni-kassel.de/url/1306b0b1855b117dc3dffeb6718ba0f3/hotho}, keywords = {2011 conference data dm ecml mining ml pkdd}, added-at = {2011-03-16T14:28:38.000+0100}, description = {}, interhash = {1306b0b1855b117dc3dffeb6718ba0f3}, intrahash = {1306b0b1855b117dc3dffeb6718ba0f3} } @electronic{www2009.eprints.org, title = {Mining Interesting Locations and Travel Sequences from GPS Trajectories}, url = {http://www2009.eprints.org/80/}, biburl = {https://puma.uni-kassel.de/url/b2a8c4242da1f7ad114f87a88d020ce0/benz}, keywords = {attended gps mining trajectory www2009}, added-at = {2011-02-04T16:08:36.000+0100}, description = {The increasing availability of GPS-enabled devices is changing the way people interact with the Web, and brings us a large amount of GPS trajectories representing people’s location histories. In this paper, based on multiple users’ GPS trajectories, we aim to mine interesting locations and classical travel sequences in a given geospatial region. Here, interesting locations mean the culturally important places, such as Tiananmen Square in Beijing, and frequented public areas, like shopping malls and restaurants, etc. Such information can help users understand surrounding locations, and would enable travel recommendation. In this work, we first model multiple individuals’ location histories with a tree-based hierarchical graph (TBHG). Second, based on the TBHG, we propose a HITS (Hypertext Induced Topic Search)-based inference model, which regards an individual’s access on a location as a directed link from the user to that location. This model infers the interest of a location by taking into account the following three factors. 1) The interest of a location depends on not only the number of users visiting this location but also these users’ travel experiences. 2) Users’ travel experiences and location interests have a mutual reinforcement relationship. 3) The interest of a location and the travel experience of a user are relative values and are region-related. Third, we mine the classical travel sequences among locations considering the interests of these locations and users’ travel experiences. We evaluated our system using a large GPS dataset collected by 107 users over a period of one year in the real world. As a result, our HITS-based inference model outperformed baseline approaches like rank-by-count and rank-by-frequency. Meanwhile, when considering the users’ travel experiences and location interests, we achieved a better performance beyond baselines, such as rank-by-count and rank-by-interest, etc.}, interhash = {b2a8c4242da1f7ad114f87a88d020ce0}, intrahash = {b2a8c4242da1f7ad114f87a88d020ce0} } @electronic{www2009.eprints.org, title = {Mining the Web 2.0 for Better Search - WWW2009 EPrints}, url = {http://www2009.eprints.org/215/}, biburl = {https://puma.uni-kassel.de/url/65b8f1b2fc9eac765435b6742e074692/benz}, keywords = {attended baeza_yates keynote mining web2.0 www2009}, added-at = {2011-02-04T16:08:35.000+0100}, description = {There are several semantic sources that can be found in the Web that are either explicit, e.g. Wikipedia, or implicit, e.g. derived from Web usage data. Most of them are related to user generated content (UGC) or what is called today the Web 2.0. In this talk we show several applications of mining the wisdom of crowds behind UGC to improve search. We will show live demos to find relations in the Wikipedia or to improve image search as well as our current research in the topic. Our final goal is to produce a virtuous data feedback circuit to leverage the Web itself.}, interhash = {65b8f1b2fc9eac765435b6742e074692}, intrahash = {65b8f1b2fc9eac765435b6742e074692} }