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26 results on '"Juffinger, Andreas"'

1. A System for Using National Bibliographies in Rights Information Infrastructures

Author

Freire, Nuno, Juffinger, Andreas, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Xing, Chunxiao, editor, Crestani, Fabio, editor, and Rauber, Andreas, editor

Published
2011
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2. Evaluation of Axiomatic Approaches to Crosslanguage Retrieval

Author

Kern, Roman, Juffinger, Andreas, Granitzer, Michael, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Peters, Carol, editor, Di Nunzio, Giorgio Maria, editor, Kurimo, Mikko, editor, Mandl, Thomas, editor, Mostefa, Djamel, editor, Peñas, Anselmo, editor, and Roda, Giovanna, editor

Published
2010
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3. Crosslanguage Retrieval Based on Wikipedia Statistics

Author

Juffinger, Andreas, Kern, Roman, Granitzer, Michael, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Peters, Carol, editor, Deselaers, Thomas, editor, Ferro, Nicola, editor, Gonzalo, Julio, editor, Jones, Gareth J. F., editor, Kurimo, Mikko, editor, Mandl, Thomas, editor, Peñas, Anselmo, editor, and Petras, Vivien, editor

Published
2009
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6. Automated Blog Classification: A Cross-Domain Approach

Author

Lex, Elisabeth, Seifert, Christin, Granitzer, Michael, Juffinger, Andreas, White, Bebo, Isaías, Pedro, and Nunes, Miguel Baptista

Subjects
ComputingMethodologies_PATTERNRECOGNITION
Abstract

The automated classification of blogs is highly important for the relatively new field of blog analysis. To classify blogs into topics or other categories, usually supervised text classification algorithms are applied. However, supervised text classifiers need a sufficient large amount of labeled data to learn a good model. Especially for blogs, data labeled with terms that capture current and actual topics are not available and data labeled in the past is usually not applicable due to topic drifts. Besides, tagged blogs collected from the web exhibit a vocabulary that is rather heterogeneous, diverse and not commonly agreed upon. In our work, we focus on news-related blogs dealing with current events. Our goal is to classify blog posts into given, common newspaper categories. As a baseline, we have high quality labeled data from a German news corpus. Our approach is to exploit the labeled data from the news corpus and use this knowledge to perform cross-domain classification on the unlabeled blogs. We need a solution with high performance, because both our corpora are dynamic and our classifier model needs to be up-to-date. In this work, we evaluated a number of text classification algorithms with different parameter settings by means of accuracy and complexity. Qualitative and quantitative analysis revealed that a recently proposed centroid-based algorithm, the Class-Feature-Centroid classifier (CFC), serves best for our setting because it achieves a comparable accuracy with state-of-the-art text classifiers and outperforms all other algorithms regarding complexity and memory consumption.

Published
2009

9. Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task

Author

KNOW CENTER GRAZ (AUSTRIA), Lex, Elisabeth, Granitzer, Michael, Juffinger, Andreas, KNOW CENTER GRAZ (AUSTRIA), Lex, Elisabeth, Granitzer, Michael, and Juffinger, Andreas

Abstract

In this paper, we outline our experiments carried out at the TREC 2009 Blog Distillation Task. Our system is based on a plain text index extracted from the XML feeds of the TREC Blogs08 dataset. This index was used to retrieve candidate blogs for the given topics. The resulting blogs were classified using a Support Vector Machine that was trained on a manually labelled subset of the TREC Blogs08 dataset. Our experiments included three runs on different features: firstly on nouns, secondly on stylometric properties, and thirdly on punctuation statistics. The facet identification based on our approach was successful, although a significant number of candidate blogs were not retrieved at all., Presented at the Text REtrieval Conference (TREC 2009, 18th) held in Gaithersburg, Maryland on 17-20 November 2009. Published in the Proceedings of the Text REtrieval Conference (TREC 2009, 18th), 2009. The conference was co-sponsored by the National Institute of Standards and Technology (NIST), the Defense Advanced Research Projects Agency (DARPA), and the Advanced Research and Development Activity (ARDA).

Published
2009

24. SPECTRAL WEB CONTENT TREND ANALYSIS.

Author

Juffinger, Andreas, Willfort, Reinhard, Lex, Elisabeth, and Granitzer, Michael

Subjects
TREND analysis, ONLINE social networks, WIKIS, BLOGS, EIGENVALUES, EIGENVECTORS
Abstract

The World Wide Web as a social network reflects changes of interest in certain domains. People use the Web to present ideas, discuss thoughts and to share knowledge. It has been shown that free online content in Blogs, Wikis, News and Forums is a valuable source of information to identify trends in certain domains. The fast amount of data makes it necessary to organize the content in taxonomies or concept networks. The size of such structures does not allow experts to identify evolving aspects directly from the networks or population labels. In this paper, we present a methodology based on data mining techniques to create a domain specific concept network. We propose spectral graph analysis on the node and edge graph to identify multi conceptional and multi relational trends. We exploit the spectrum to cluster the difference graph and to highlight the changed concept network regions. The spectrum distance is further used to quantify the trend impact. Experiments on synthetic and real-world networks showed that with the proposed methodology complex multi conceptional and relational trend analysis can be performed. [ABSTRACT FROM AUTHOR]

Published
2009

25. Automated Ontology Learning and Validation Using Hypothesis Testing.

Author

Kacprzyk, Janusz, Węgrzyn-Wolska, Katarzyna M., Szczepaniak, Piotr S., Granitzer, Michael, Scharl, Arno, Weichselbraun, Albert, Neidhart, Thomas, Juffinger, Andreas, and Wohlgenannt, Gerhard

Abstract

Semantic Web technologies in general and ontology-based approaches in particular are considered the foundation for the next generation of information services. While ontologies enable software agents to exchange knowledge and information in a standardized, intelligent manner, describing todayŠs vast amount of information in terms of ontological knowledge remains a challenge. In this paper we describe the research project AVALON - Acquisition and VAL-idation of ONtologies, which aims at reducing the knowledge acquisition bottleneck by using methods from ontology learning in the context of a cybernetic control system. We will present techniques allowing us to automatically extract knowledge from textual data and formulating hypothesis based upon the extracted knowledge. Based on real world indicators, like for example business numbers, hypotheses are validated and the result is fed back into the system, thereby closing the cybernetic control system's feedback loop. While AVALON is currently under development, we will present intermediate results and the basic idea behind the system. [ABSTRACT FROM AUTHOR]

Published
2007
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26. Guest Editorial.

Author

Knoth, Petr, Zdrahal, Zdenek, and Juffinger, Andreas

Subjects
DATA mining, DATA analysis, TRENDS
Abstract

The editor introduces the research projects within the issue, which were presented at the International Workshop on Mining Scientific Publications held during the 2012 Joint Conference on Digital Libraries, and which discuss data analysis, semantic enrichment, and identification of research trends.

Published
2012
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