The BBC blog about the project Vista-TV in which Libby Miller shows visualizations of user behavior. (Weiter...  )

The goal of the International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, UBICOMM 2013, is to bring together researchers from the academia and practitioners from the industry in order to address fundamentals of ubiquitous systems and the new applications related to them. The conference will provide a forum where researchers shall be able to present recent research results and new research problems and directions related to them. The conference seeks contributions presenting novel research in all aspects of ubiquitous techniques and technologies applied to advanced mobile applications.

Deadline: 17. May 2013

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Der Lehrstuhl für künstliche Intelligenz sucht zum nächstmöglichen Zeitpunkt (01.08.13) zwei wissenschaftliche Beschäftigte. (Weiter...  )

An der TU Dortmund, Fakultät für Informatik am Lehrstuhl VIII sind ab sofort Stellen für Studentische Hilfskräfte im Umfang von bis zu 10 Wochenstunden zu besetzen. (Weiter...  )

LS8 analysis football games in realtime! Each player is equipped with a sensor and so is the ball. The streams framework from LS8 is coupled with the Esper event recognition of Technion. (Weiter...  )

Fernsehen über das Internet (IP-TV) spielt eine immer größere Rolle in der heutigen Medienlandschaft. Größere Programmvielfalt, Fernsehen auf mobilen Geräten, oder Mediatheken sind nur ein paar Vorzüge de neuen Fernsehwelt. Um das TV-Erlebnis für jeden Zuschauer zu optimieren ist im Hintergrund jede Menge Hightech gefragt. Das EU-Projekt ViSTA-TV erforscht das TV-Verhalten von Benutzern, sucht nach ähnlichen Sendungen und versucht so, dem Zuschauer das bestmögliche Programm zu empfehlen. Von der Lieblingssendung zu interessanten Dokumentationen oder die neuesten Trends - in der Fülle der Angebote wird für jeden Zuschauer das richtige gefunden.

Das Projekt ViSTA-TV ist ein Gemeinschaftsprojekt der Universitäten Zürich, Amsterdam und des Lehrstuhl 8 der Informatik der TU Dortmund, sowie den Unternehmen BBC, Zattoo und der Dortmunder Firma Rapid-I. Ziel des Projektes ist die Analyse des Fernsehverhaltens von IPTV Nutzern um z.B. Empfehlungen von Sendungen möglichst genau an die Bedürfnisse und Vorlieben der Zuschauer anzupassen. Dafür wird das Ein- und Umschaltverhaltens der Benutzer, sowie Eigenschaften des Video-Signals (zB. Werbungserkennung) analysiert.

Eine Herausforderung stellt dabei die große Datenrate von Video-Daten, die in Echtzeit analysiert werden müssen. Dazu wurde die Datenstrom-Umgebung „streams“, die von Christian Bockermann am Lehrstuhl 8 entwickelt wurde, um die Fähigkeit der Video-Analyse erweitert. Dies ermöglicht die gleichzeitige Analyse von Video-Daten mit dem dazugehörigen Umschaltverhalten aus Log-Daten. Die Ergebnisse werden dann innerhalb eines Empfehlungssystems weiter verarbeitet um Nutzern einen maßgeschneiderten Blick auf das TV-Angebot zu bieten.

Mit im Blick haben die Forscher aus Dortmund dabei natürlich auch die Integra-tion weiterer Datenquellen, wie DBpedia, elektronische Fernsehzeitschriften oder die beliebte Internet Movie Database (imdb). Im Sinne des „Big Data“ Gedankens, werden alle diese Informationen zeitnah analysiert und lassen so auch Informationen über Schauspieler, Nachrichten oder aktuelle Trends auf Twitter und facebook mit in die Empfehlungen einfließen.


Coding-Camp an der TU

In dieser Woche findet im an der TU Dortmund das zweite Coding-Camp zum ViSTA-TV Projekt statt. Dabei stehen insbesondere die Integration der Module der Projektpartner im Mittelpunkt. Das Ziel des Coding-Camp ist ein erster lauffähiger Prototyp des Projektes, der Programmempfehlungen an Zuschauer über Handy-Apps anbietet.

Am 19. Februar findet in Dortmund der Regionalwettbewerb Jugend forscht statt. In den Räumen der DASA Arbeitswelt Austellung präsentieren die jungen Nachwuchsforscher ihre Ideen und Arbeiten in verschiedenen Forschungsgebieten der Jury. Für das Gebiet Mathematik/Informatik ist mit Christian Bockermann auch der Lehrstuhl 8 der Fakultät für Informatik und ein Mitarbeiter im Projekt C1 des SFB in der Jury vertreten.

The book Managing and Mining Sensor Data has been published as an ebook and will be available as hardcover from 28th of February 2013. The book has been supported by the collaborative research center by the authors Marco Stolpe (project B3, Artificial Intelligence) and the guest researcher Kanishka Bhaduri. They contributed the chapter on Distributed Data Mining in Sensor Networks.

Especially sensor networks provide data at different, distributed locations. For an efficient analysis new technologies need to calculate results even if communication ressources are constrained.

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Katharina Morik organizes a Panel on the value of data at the IEEE International Conference on Data Mining (Weiter...  )

Der Lehrstuhl für künstliche Intelligenz sucht zum nächstmöglichen Zeitpunkt zwei wissenschaftliche Beschäftigte.

• Für das Projekt DDMD (Data Driven Materials Development) wird ein/eine (Post-)Doktorand/in gesucht. Das Projekt läuft in Zusammenarbeit mit Univ. Duisburg-Essen und RUB. Weitere Details können der Ausschreibung entnommen werden.
• Für das Projekt KobRA (Korpus-basierte linguistische Recherche und Analyse mit Hilfe von Data-Mining) wird ebenfalls eine/ein wissenschaftliche/r Beschäftigte/r gesucht. Dabei soll die Korpus-basierte Linguistik durch Methoden des Data Mining unterstützt werden. Weitere Details können der Ausschreibung entnommen werden.

The German newspaper "Westdeutsche Allgemeine Zeitung" has published an article about Katharina Morik. The full article can be found on their website. (Weiter...  )

Im Anwendungsfall energie- und ressourcenintensiver Industrien besteht die Herausforderung darin, steigende Produktqualität bei gleichzeitiger Reduzierung von Kosten und Produktionszeiten zu realisieren. Prinzipien und Methoden von Qualitätsmanagement- und Produktionssystemen nach dem Vorbild der japanischen Automobilindustrie rücken dabei als vorrangiges Leitbild branchenübergreifend in den Mittelpunkt. Als ein wesentliches Element des TPS leistet das Prinzip einer prozessimmanenten Qualitätskontrolle, auch bekannt unter den Begriffen Jidoka oder Autonome Automation, einen entscheidenden Beitrag. Jedoch ist das Jidoka-Prinzip im Fall automatisierter, verketteter Produktionsprozesse, wie sie beispielsweise in der Stahlindustrie vorzufinden sind, auf konventionellem Weg nicht ohne weiteres realisierbar.

Ziel dieses Promotionsvorhabens ist die Entwicklung und Validierung einer Systematik zur Ausschussminimierung und Produktqualitätsoptimierung im Kontext starr verketteter, automatisierter Produktionsprozesse. Ein möglicher Ansatz stellt dabei das Konzept der Advanced Process Control dar. Zentraler Gedanke ist dabei die realzeitliche, prozessdatenbasierte Überwachung und Auswertung von Produktionsprozessen mit dem Ziel, kurzfristige Prozessschwankungen ausgleichen und somit die Produktqualität sicherstellen zu können. Das Promotionsvorhaben soll für das oben skizzierte Produktionssystem einen Ansatz entwickeln, der basierend auf der automatisierten Auswertung von Prozessparametern entscheidet, ob die Qualität des aktuell bearbeiteten Produkts den Spezifikationen entspricht oder ob und in welcher Form eine Anpassung der Prozessparameter erforderlich und realzeitlich möglich ist, um die Qualitäts­spezifikationen zu erfüllen. Alternativ besteht eine weitere Entscheidungsmöglichkeit darin, das Produkt nicht weiter zu bearbeiten, wenn die Qualitätsabweichung durch Anpassung des Produktionsprozessablaufes nicht korrigiert werden kann.

Die Durchführung des Vorhabens umfasst neben der Entwicklung des theoretischen Konzeptes, eine simulationsbasierte Validierung sowie in enger Kooperation mit der Deutsche Edelstahlwerke GmbH am Standort Witten die Integration des Konzeptes in die betrieblichen Produktionsabläufe. Zur Lösung der Aufgabe soll auf den Einsatz modernster Data Mining-Techniken zurückgegriffen werden.

Betreuer: Prof. Deuse

Bewerbungen ab sofort an:

Dipl.-Wirt.-Ing. Uta Spörer
Tel.: +49 (231) 755 – 5787
Fax: +49 (231) 755 – 5772
E-Mail: spoerer@gsoflog.de
Mo- Do: 8:30 - 12:30 Uhr

 

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LWA stands for "Lernen, Wissen, Adaption" (Learning, Knowledge, Adaptation). It is the joint forum of four special interest groups of the German Computer Science Society (GI). Following the tradition of the last years, LWA provides a joint forum for experienced and for young researchers, to bring insights to recent trends, technologies and applications, and to promote interaction among the SIGs. (Weiter...  )

• SURVEY & PARTICIPANTS: 52-item survey of data miners, conducted on-line in 2011. Participants: 1,319 data miners from over 60 countries.
• FIELDS & GOALS: Data miners work in a diverse set of fields. CRM/Marketing has been the #1 field for the past five years. Fittingly, “improving the understanding of customers”, “retaining customers” and other CRM goals continue to be the goals identified by the most data miners.
• ALGORITHMS: Decision trees, regression, and cluster analysis continue to form a triad of core algorithms for most data miners. However, a wide variety of algorithms are being used. A third of data miners currently use text mining and another third plan to do so in the future.
• TOOLS: R continued its rise this year and is now being used by close to half of all data miners (47%). R users report preferring it for being free, open source, and having a wide variety of algorithms. Many people also cited R's flexibility and the strength of the user community. STATISTICA is selected as the primary data mining tool by the most respondents (17%). Data miners report using an average of 4 software tools. STATISTICA, KNIME, Rapid Miner and Salford Systems received the strongest satisfaction ratings in 2011.
• ANALYTIC CAPABILITY & SUCCESS MEASUREMENT: Only 12% of corporate respondents rate their company as having very high analytic sophistication. However, companies with better analytic capabilities are outperforming their peers. Respondents report analyzing analytic success via Return on Investment (ROI) and analyzing the predictive validity or accuracy of their models. Challenges to measuring success include client or user cooperation and data availability/quality.
• SHARED INSIGHTS: In the 2010 Survey data miners shared best practices in overcoming the key challenges data miners face ( verbatims ). In the 2011 Survey data miners shared their best practices for measuring analytic success ( verbatims ) and examples of the positive impact that data mining can have to benefit society, health, and the world ( verbatims ). Additionally, 225 R users shared information about how and why they are using R ( verbatims ).

After the 2011 survey, Rexer Analytics Data Miner Survey has moved to a bi-annual schedule; the next Data Miner Survey will be launched in early 2013. Information about Rexer Analytics is available at www.RexerAnalytics.com (Weiter...  )

The grant application Data Driven Materials Design (DDMD) was granted in line with the 4th call for proposals of the Mercator Research Center Ruhr (MERCUR). The project is a cooperation between Prof. Dr. Ralf Drautz, Prof. Dr. Alfred Ludwig, (both Ruhr-University Bochum), Prof. Dr. Katharina Morik (Chair 8) and Prof. Dr. Sven Rahmann (University Duisburg-Essen). The connected usage of experimental high-through-put-methods and analytic modeling in materials research, especially in the fields of thin-layer-material-libraries, "Attribute-Screenings" and "Advance Materials Simulation", is one of Ruhr-University's unique features, which is intended to be strengthened with this application. The mentioned fields have in common that they generate an extremely huge amount of multidimensional data that can not be analyzed efficiently without the help of computers. Analyzing huge amounts of data is one of TU Dortmund's focuses of which in this case particularly Data Mining is addressed. At Univerity Essen-Duisburg high-through-put-analysis is in front. The intention of this colaboration is to initiate a more rational development of new materials. The application tends to establish the foundation for the field of Data Driven Material Development. In this field new discoveries as well as new comprehensions (e.g. unknown phases or special physical properties) are supposed to be gained. In addition the development of new materials is to be speeded up. (Weiter...  )

The application "INtelligent Synthesis and Real-tIme Response using Massive StreaminG of HeTerogeneous Data" is the best rated one in field FP7 "Intelligent Information Management" reaching 14.5 of possible 15 points. The Department of Computer Science at the TU Dortmund is involved with chair 8. Coordinator is Dimitrios Gunopulos (National University Athen). It is about analysing the huge amount of heterogeneous datastreams from sensors, mobile phones and control systems to enhance the management of cases of emergency. Examples are taken from the city of Dublin and the german Federal Office of Civil Protection and Disaster Assistance. The innovation of Data Mining finally enabled analysing social networks (e.g. Twitter), sensor-networks, and traffic-systems in connection and integrating citizens in this process.

Live video content is increasingly consumed over IP networks in addition to traditional broadcasting. The move to IP provides a huge opportunity to discover what people are watching in much greater breadth and depth than currently possible through interviews or set-top box based data gathering by rating organizations. The ViSTA-TV project proposes to gather consumers’ anonymized viewing behavior and the actual video streams combined with enhanced electronic program guide information. ViSTA-TV will be in the position to provide highly accurate market research information about viewing behavior that can be used for a variety of analyses of high interest to all participants in the TV-industry. Furthermore ViSTA-TV will employ the information gathered to build a recommendation service. ViSTA-TV is an European Union-funded research project, beginning on 1 June 2012, and lasting for two years. The Artificial Intelligence Group participates alongside 5 other partners. (Weiter...  )

Rapid-I is based in Dortmund, Germany, and has been working on RapidMiner, a Data-Mining-Software, since 2001. With its wide range of other tools such as RapidAnalytics, RapidLab, RapidNet and RapidSentilyzer it could win over such clients as Siemens, Allianz and Pepsico. The website JTonEDM.com introduces Rapid-I and its software RapidMiner in a short overview. (Weiter...  )

In heutigen Industrieanlagen zeichnen Sensoren während des Produktionsprozesses große Mengen an Daten auf. Aus diesen Daten wird schon während des laufenden Prozesses auf die Qualität des Endprodukts geschlossen. Produktionsbedingt kommt es während des laufenden Prozesses zu Veränderungen von Anlagenkomponenten und Messtechnik, die nur zyklisch instand gehalten werden können. Die Veränderungen spiegeln sich auch in den Prognosemodellen wieder. Es kommt zum Concept Drift. SMS Siemag und ein führender Hersteller von Grobblechen stellen für diese Arbeit aktuelle Produktionsdaten zur Verfügung. Im Rahmen der Bachelor, Diplom- oder Masterarbeit sollen Strategien zur Identifizierung von Concept Drifts und zur Stabilisierung der Prognosegüte entwickelt werden. Eine besondere Herausforderung stellt es dar, dass die Concept Drift Erkennung und Bereinigung in Realzeit geschehen soll. Der Schwerpunkt der Arbeit liegt daher auf der Auswahl, der Implementierung und dem Vergleich besonders effizienter Verfahren zur Entdeckung von Concept Drifts. (Weiter...  )

In heutigen Industrieanlagen zeichnen Sensoren während des Produktionsprozesses große Mengen an Daten auf. Aus diesen Daten wird schon während des laufenden Prozesses auf die Qualität des Endprodukts geschlossen. Bisher wird von der Optimierung meist nur eine Zielgröße behandelt. Die Qualität des Endproduktes hängt aber oft von mehreren Zielgrößen ab, die sich obendrein widersprechen können. Dies kann nun als multikriterielles Optimierungsproblem formalisiert werden. Insbesondere muss eine geeignete Fitnessfunktion bestimmt werden. Dann können die Anwender aus den pareto-optimalen Lösungen Handlungsempfehlungen ableiten. Am LS8 stehen Sensordaten über den Produktionsprozess eines führenden Herstellers von Grobblechen zur Verfügung. An diesem Beispiel kann die Formalisierung von widersprüchlichen Zielgrößen als multikriterielle Optimierung untersucht werden. Dabei können Implementierungen in Rapid-Miner genutzt werden. Die genaue Aufgabenstellung wird darauf angepasst, ob es eine Bachelor, Diplom- oder Masterarbeit wird. (Weiter...  )

Together with Kanishka Bhaduri and Hillol Kargupta, Katharina Morik has edited a special issue of the international journal Data Mining and Knowledge Discovery. The special issue on Data Mining for Sustainability including a comprehensive introduction is now online at http://www.springerlink.com/. (Weiter...  )

Die Projektgruppe "Kooperatives Datamining mit vernetzen Robotern" wird am 22.12.2011 um 14:00 Uhr (s.t.) in den neuen Räumlichkeiten des Lehrstuhls 8 (Joseph-von-Frauenhofer Straße 23 in Raum 1.48) präsentiert.

Die Suche und Buchung von Hotels über das Internet wird heute üblicherweise über spezielle Portale abgewickelt. Die reine Filterung anhand von Suchkriterien führt häufig zur Ausgabe einer noch immer unüberschaubaren Anzahl von Hotels. Für die langfristige Bindung von Kunden an ein Portal ist es jedoch entscheidend, so schnell wie möglich Hotels anbieten zu können, die für die jeweilige Person (oder Personengruppe) tatsächlich geeignet sind. Mittels Methoden des Data Minings und maschinellen Lernens sollen Benutzerpräferenzen gelernt werden, die personalisierte und damit geeignetere Empfehlungen von Hotels ermöglichen. Hierzu werden vom weltweit führenden Portalbetreiber "Hotel Reservation Service" (HRS) Daten über Hotels, Portalbesucher, Kunden, Buchungen und Hotelbewertungen zur Verfügung gestellt. (Weiter...  )

The annual ACM SIGKDD conference is the premier international forum for data mining researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. KDD-2011 will feature keynote presentations, oral paper presentations, poster sessions, workshops, tutorials, panels, exhibits, demonstrations, and the KDD Cup competition. KDD-2011 will run from August 21-24 in San Diego, CA and will feature hundreds of practitioners and academic data miners converging on the one location. (Weiter...  )

Being in the editorial boards of Knowledge and Information Systems (KAIS) and of Data Mining and Knowledge Discovery (DMKD), Katharina Morik happily presents the impact factors (2010) of some leading database and data mining journals:

• ACM Transactions on Information Systems (TOIS): 1.085
• ACM Transactions on Database Systems (TODS): 1.216
• Data Mining and Knowledge Discovery (DMKD): 1.238
• Information Systems (IS): 1.595
• Data and Knowledge Engineering (DKE): 1.717
• IEEE Transactions on Knowledge and Data Engineering (TKDE): 1.847
• Machine Learning (ML): 1.956
• Knowledge and Information Systems (KAIS): 2

Download the complete list

Neben YouTube und Co. wird das Internet mit zunehmender Bandbreite auch für klassisische Fernsehübertragungen immer interessanter. War IP-TV bisher meist für große Sportereignisse im Fokus, bieten Firmen wie z.B. zattoo.com bereits die Möglichkeit sich einer Vielzahl unterschiedlicher Kanäle zu bedienen, Sendungen online aufzuzeichnen und zu Archivieren. Aber wie findet man interessante Sendungen? Welche Informationen geben Aufschluß über Programme die mir gefallen? Lassen sich Spartensender allein anhand der Informationen aus den Video-Daten unterscheiden? In dieser Master-Arbeit geht es um die Extraktion von Merkmalen, die für die Klassifikation oder die Gruppierung von Sendungen, Sendern oder Fernsehzuschauern wichtig sind. (Weiter...  )

The Feature Selection Extension für RapidMiner 5 contains some operators for feature selection and -weighting and for classification. All operators are also highly suitable for high-dimensional data, e.g. microarray data. New in this version are:

• RCCW - Recursive Conditional Correlation Weighting a very fast feature subset selection method.
• FCBF - Fast Correlation Based Feature Selection
• PAM - Classification by Shrunken Centroids
• BAHSIC - Backward Feature Selection via Hilbert-Schmidt information criterion
• t-Test - Computes a p-Value for the difference of the mean values between two classes
• Test Significance - Assumes normal distribution, then checks for equal class variances via F-test and afterwards computes p-Value via t-Test or Welch-test
• Benjamini-Hochberg-Correction - Performs the correction for FDR on significance values in an AttributeWeights object

Already available since older version are - amongst others - Recursive Feature Elimination (RFE) and minimum Redundancy Maximum Relevance Feature Selection (MRMR) / Correlation based Feature Selection (CFS) and a meta-operator for ensemble feature selection. The most recent version is available for free from SourceForge: https://sourceforge.net/projects/rm-featselext/ . (Weiter...  )

RapidMiner is again the most popular data mining tool in KDnuggets poll. (Weiter...  )

Graphics processor (GPU) architectures have evolved rapidly in recent years with increasing performance demanded by 3D graphics applications such as games. However, challenges exist in integrating complex GPUs into mobile devices because of power and energy constraints, motivating the need for energy efficiency in GPUs. While a significant amount of power optimisation research effort has concentrated on the CPU system, GPU power efficiency is a relatively new and important area because the power consumed by GPUs is similar in magnitude to CPU power. Power and energy efficiency can be introduced into GPUs at many different levels: (i) Hardware component level - queue structures, caches, filter arithmetic units, interconnection networks, processor cores, etc., can be optimised for power. (ii) Algorithm level - the deep and complex graphics processing computation pipeline can be modified to be energy aware. Shader programs written by the user can be transformed to be energy aware. (iii) System level - co-ordination at the level of task allocation, voltage and frequency scaling, etc., requires knowledge and control of several different GPU system components. (Weiter...  )

An increasing amount of information is being encoded via ontologies and knowledge representation languages of some sort. Some of these knowledge bases are encoded manually, while others are generated automatically by information extraction techniques. In order to protect the confidentiality of this information, a natural choice consists in encoding policies with the same language as the ontology language. This approach led to so-called "semantic web policies". The semantic web is founded on two knowledge representation languages: description logics and logic programs. In this talk we compare their expressive power as *policy* representation languages, and show that logic programming approaches are currently more mature than description logics, although this picture may change in the near future. (Weiter...  )

Emerging and envisioned applications within domains such as indoor navigation, fire-fighting, and precision agriculture still pose challenges for existing positioning solutions to operate accurately, reliably, and robustly in a variety of environments and conditions and under various application-specific constraints. This talk will first give a brief overview of efforts made in a Danish project to address challenges as mentioned above, and will subsequently focus on addressing the energy constraints imposed by Location-based Services (LBS), running on mobile user devices such as smartphones. A variety of LBS, including services for navigation, location-based search, social networking, games, and health and sports trackers, demand the positioning and trajectory tracking of smartphones. To be useful, such tracking has to be energy-efficient to avoid having a major impact on the battery life of the mobile device, since the battery capacity in modern smartphones is a scarce resource, and is not increasing at the same pace as new power-demanding features, including various positioning sensors, are added to such devices. We present novel on-device sensor management and trajectory updating strategies which intelligently determine when to sample different on-device positioning sensors (accelerometer, compass and GPS) and when data should be sent to a remote server and to which extent to simplify it beforehand in order to save communication costs. The resulting system is provided as uniform framework for both position and trajectory tracking and is configurable with regards to accuracy requirements. The effectiveness of our approach and the energy savings achievable are demonstrated both by emulation experiments using real-world data and by real-world deployments. (Weiter...  )

• Program

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Stefan Manegold from CWI Amsterdam will be giving a talk on the column-store DBMS MonetDB on 2011/02/11 um 16.00 at Room E23, Otto-Hahn-Straße 14.

Abstract:
Column-store database management systems have recently experienced a considerable popularity-boost. The underlying ideas, however, date back to (at least) the mid 1980's and the technology has been pioneered since the early 1990's in the MonetDB system, a column-store research prototype that has been developed into a complete SQL- and XML/XQuery-compliant column-store DBMS freely available in open source. Next to its column-store back-bone, MonetDB focuses on high-performance hardware-conscious algorithms, novel workload-adaptive query processing techniques such as "cracking", "recycling" and run-time query optimization, and extensibility at all layers of its software stack.

In this talk, we will provide detailed insight into MonetDB's column-store architecture and query-processing technology as available in open-source, discussing its benefits for data mining, OLAP, BI, as well as science workloads.

The new Collaborative Research Center SFB 876 "Providing Information by Resource-Constrained Data Analysis" starts the new year with a kick-off colloquium. The colloquium takes place on January 20th 2011 starting at 4 pm at auditorium E23, Otto-Hahn-Straße 14, TU Dortmund University campus. For further information about the program and speeches please have a look at the attachment.

• Schedule
• Monitoring the Data Tsunami (Johannes Gehrke) , Download slides
• Model predictive control and self-learning of thermal models for thermal control for multi-core platforms (Luca Benini) , Download slides

At this time, no futher applications for open positions at the SFB 876 are being accepted.

The DFG granted the SFB 876. (Weiter...  )

First presentations and pictures available on the MODAP workshop website. (Weiter...  )

Analyzing huge amounts of mobility data has posed new challenges not only in the discovery and interpretation of interesting patterns, but also in the privacy preservation of individuals under observation. However, the social and privacy aspects of mobility have not been studied in a systematic and combinatorial way, while the census and the conception of their effects in our lives is rather in childhood. The convergence of these complementary aspects, and more specifically, the way that mobility affects (or is affected by) the social behavior of individuals and their privacy, emerges the exciting new area of "socio-mobility". Socio-mobility arises a number of challenging questions. Are people moving together socially related? Are there social relations between people moving to semantically similar places? How could we combine mobility data and patterns with social networking information? Can social interactions be mined from mobility data by using external media? To what extend do social interactions affect privacy? What are the risks of disclosing social interactions between people and how can we design privacy-preserving techniques to minimize the risks? What kinds of social interactions are considered sensitive and how can we model / distort / suppress such interactions? (Weiter...  )

The Interdisciplinary College (IK) is an annual, intense one-week spring school which offers a dense state-of-the-art course program in neurobiology, neural computation, cognitive science/psychology, artificial intelligence, robotics and philosophy. It is aimed at students, postgraduates and researchers from academia and industry. (Weiter...  )

The student project group 542 "Stream Mining for Intrusion Detection in Distributed Systems" has succesfully finished their work on a generic framework for online and distributed data mining. All results including system's architecture, evluation of learning algorithms and a live demo covering the use case of intrusion detection will be presented on Thursday, 28th October, 10.15 at GB 4 room 136. (Weiter...  )

After presenting our paper "Implementing Hierarchical Heavy Hitters in RapidMiner: Solutions and Open Questions" at the RCOMM 2010, we have released all accompanying Java code as RapidMiner 5 plugin. The plugin can be used to calculate Hierarchical Heavy Hitters on system call data. It furthermore contains domain-independent implementations of the related algorithms in Java. (Weiter...  )

The Microarray Feature Selection Plugin for RapidMiner 5 contains some feature selection and -weighting operators useful for working on high-dimensional (microarray-) data. These are - amongst others - Recursive Feature Elimination (RFE) and minimum Redundancy Maximum Relevance Feature Selection (MRMR) / Correlation based Feature Selection (CFS) and a meta-operator for ensemble feature selection. (Weiter...  )

The RapidMiner Information Extraction extension supports Information Extraction techniques in RapidMiner. Visualizers, annotators and preprocessing operators have been implemented for textual purpose. Structured models - namely Conditional Random Fields - for the extraction of named entities are available. Operators to extract relations with will be available soon. (Weiter...  )

The 1st Summer School on Mobility, Data Mining, and Privacy is co-organized by the FP7/ICT project MODAP "Mobility, Data Mining, and Privacy" (www.modap.org) and the COST Action IC0903 MOVE "Knowledge Discovery from Moving Objects" (http://move-cost.info/). This is the first doctoral school ever on the 'hot' intersection of three domains: modeling and management of moving object databases (Mobility), data analysis and knowledge discovery from mobility data (Data Mining), and privacy aspects that raise when processing human mobility (Privacy). (Weiter...  )

Knowledge discovery in ubiquitous environments is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. The new book, edited by Michael May and Lorenza Saitta, provides a state-of-the-art survey. It is the outcome of a large number of workshops, summer schools, tutorials and dissemination events of the European project KDubiq. (Weiter...  )

Bringing together embedded systems and data mining enables new solutions in computer science, bio medicine, physics and mechanical engineering. Embedded system can be further improved using machine learning while data mining algorithms can be realized in hardware, e.g. FPGAs. The restrictions in computing power, memory and energy demands new algorithms for known learning tasks. At Bommerholz 26 scientists and researchers from TU Dortmund and University Duisburg-Essen came together to gain a deeper understanding of the topic and exchange progress of ongoing projects.

RapidMiner is the most successful open source data mining tool for the third year in series -- only the commercial product Clementine (SPSS PASW Modeler) is more popular. (Weiter...  )

Asian Conference on Machine Learning
November 8-10, 2010, Tokyo, Japan (Weiter...  )

Special Issue on Sustainability of the Data Mining and Knowledge Discovery Journa (Weiter...  )

Katharina Morik "Handling Texts -- A Challenge for Data Mining" talk (in English), introduced by Jean-Gabriel Ganascia on the 9th francophone expert conference on Machine Learning and Data Mining, Strasbourg 2009

(Needs Microsoft Media Player Plugin):
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Lecture of Yoav Freund at the ECML PKDD 2008 about machine learning and biology

BioDatatbases(bioDatabases.m4v, 170.6 MB)

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Based on the experiences of the 1999 lecture DAP1 a new textbook has finally arisen. This book introduces the fundamentals of the common core of different computer science areas by means of the programming language JAVA. (Weiter...  )

Prof. Dr. Katharina Morik was asked for a statement about equal opportunity for women.

The resulting TV report was shown on 07/11/2007 during the "tagesschau" news broadcast.

Source: Tagesschau-archive

Several programs have been developed at the AI unit within its research activities, such as myKLR, SVM^light, mySVM, RapidMiner (formerly YALE), the Information Layer or the USCHIFICATOR. Check our software page for a complete list. (Weiter...  )