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(Schlagwörter: "Data Mining")
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Mining positional data streams
Haase, Jens; Brefeld, Ulf
Book Chapter
| Aus: Appice, Annalise;Ceci, Michelangelo; Loglisci, Corrado;Manco, Guiseppe; Masciari, Elio; Ras, Zbigniew W. (Hrsg.): New frontiers in mining complex patterns: Third International Workshop, NFMCP 2014, held in conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers | Cham: Springer | 2015
35622 Endnote
Author(s):
Haase, Jens; Brefeld, Ulf
Title:
Mining positional data streams
In:
Appice, Annalise;Ceci, Michelangelo; Loglisci, Corrado;Manco, Guiseppe; Masciari, Elio; Ras, Zbigniew W. (Hrsg.): New frontiers in mining complex patterns: Third International Workshop, NFMCP 2014, held in conjunction with ECML-PKDD 2014, Nancy, France, September 19, 2014, Revised Selected Papers, Cham: Springer, 2015 (Lecture notes in computer science, 8983), S. 102-116
DOI:
10.1007/978-3-319-17876-9
Publication Type:
4. Beiträge in Sammelwerken; Sammelband (keine besondere Kategorie)
Language:
Englisch
Keywords:
Algorithmus; Bewegung <Motorische>; Data Mining; Daten
Abstract:
We study frequent pattern mining from positional data streams. Existing approaches require discretised data to identify atomic events and are not applicable in our continuous setting. We propose an efficient trajectory-based preprocessing to identify similar movements and a distributed pattern mining algorithm to identify frequent trajectories. We empirically evaluate all parts of the processing pipeline. (DIPF/Orig.)
DIPF-Departments:
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Linking the thoughts. Analysis of argumentation structures in scientific publications
Kirschner, Christian; Eckle-Kohler, Judith; Gurevych, Iryna
Book Chapter
| Aus: Association for Computational Linguistics (Hrsg.): Proceedings of the 2nd Workshop on Argumentation Mining held in conjunction with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT 2015) | Denver; CO: Association for Computational Linguistics | 2015
35503 Endnote
Author(s):
Kirschner, Christian; Eckle-Kohler, Judith; Gurevych, Iryna
Title:
Linking the thoughts. Analysis of argumentation structures in scientific publications
In:
Association for Computational Linguistics (Hrsg.): Proceedings of the 2nd Workshop on Argumentation Mining held in conjunction with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL HLT 2015), Denver; CO: Association for Computational Linguistics, 2015 , S. 1-11
URL:
https://aclweb.org/anthology/W/W15/W15-05.pdf
Publication Type:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Argumentation; Automatisierung; Bildungsforschung; Computerlinguistik; Data Mining; Klassifikation; Textanalyse; Veröffentlichung
Abstract:
This paper presents the results of an annotation study focused on the fine-grained analysis of argumentation structures in scientific publications. Our new annotation scheme specifies four types of binary argumentative relations between sentences, resulting in the representation of arguments as small graph structures. We developed an annotation tool that supports the annotation of such graphs and carried out an annotation study with four annotators on 24 scientific articles from the domain of educational research. For calculating the inter-annotator agreement, we adapted existing measures and developed a novel graph based agreement measure which reflects the semantic similarity of different annotation graphs. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
DKPro TC. A Java-based framework for supervised learning experiments on textual data
Daxenberger, Johannes; Ferschke, Oliver; Gurevych, Iryna; Zesch, Torsten
Book Chapter
| Aus: Bontcheva, Kalina; Jingbo, Zhu (Hrsg.): Proceedings of COLING 2014: System demonstrations | Stroudsburg; PA: Association for Computational Linguistics | 2014
34721 Endnote
Author(s):
Daxenberger, Johannes; Ferschke, Oliver; Gurevych, Iryna; Zesch, Torsten
Title:
DKPro TC. A Java-based framework for supervised learning experiments on textual data
In:
Bontcheva, Kalina; Jingbo, Zhu (Hrsg.): Proceedings of COLING 2014: System demonstrations, Stroudsburg; PA: Association for Computational Linguistics, 2014 , S. 61-66
URL:
http://aclweb.org/anthology/P/P14/P14-5011.pdf
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Automatisierung; Computerlinguistik; Computerprogramm; Data Mining; Datenverarbeitung; Klassifikation; Programmiersprache; Text; Textanalyse
Abstract:
We present DKPro TC, a framework for supervised learning experiments on textual data. The main goal of DKPro TC is to enable researchers to focus on the actual research task behind the learning problem and let the framework handle the rest. It enables rapid prototyping of experiments by relying on an easy-to-use workflow engine and standardized document preprocessing based on the Apache Unstructured Information Management Architecture (Ferrucci and Lally, 2004). It ships with standard feature extraction modules, while at the same time allowing the user to add customized extractors. The extensive reporting and logging facilities make DKPro TC experiments fully replicable. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
An off-the-shelf approach to authorship attribution
Nasir, Jamal A.; Görnitz, Nico; Brefeld, Ulf
Book Chapter
| Aus: Dublin City University and Association for Computational Linguistics (Hrsg.): Proceedings of COLING 2014: Technical papers | Stroudsburg; PA: Association for Computational Linguistics | 2014
35007 Endnote
Author(s):
Nasir, Jamal A.; Görnitz, Nico; Brefeld, Ulf
Title:
An off-the-shelf approach to authorship attribution
In:
Dublin City University and Association for Computational Linguistics (Hrsg.): Proceedings of COLING 2014: Technical papers, Stroudsburg; PA: Association for Computational Linguistics, 2014 , S. 895-904
URL:
http://www.aclweb.org/anthology/C14-1085
Publication Type:
4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Language:
Englisch
Keywords:
Algorithmus; Automatisierung; Autor; Computerunterstütztes Verfahren; Data Mining; Datenverarbeitung; Information Retrieval; Methode
Abstract:
Authorship detection is a challenging task due to many design choices the user has to decide on. The performance highly depends on the right set of features, the amount of data, insample vs. out-of-sample settings, and profile- vs. instance-based approaches. So far, the variety of combinations renders off-the-shelf methods for authorship detection inappropriate. We propose a novel and generally deployable method that does not share these limitations. We treat authorship attribution as an anomaly detection problem where author regions are learned in feature space. The choice of the right feature space for a given task is identified automatically by representing the optimal solution as a linear mixture of multiple kernel functions (MKL). Our approach allows to include labelled as well as unlabelled examples to remedy the in-sample and out-of-sample problems. Empirically, we observe our proposed novel technique either to be better or on par with baseline competitors. However, our method relieves the user from critical design choices (e.g., feature set) and can therefore be used as an off-the-shelf method for authorship attribution. (DIPF/Orig.)
DIPF-Departments:
Informationszentrum Bildung
The people's web meets NLP. Collaboratively Constructed Language Resources
Gurevych, Iryna; Kim, Jungi (Hrsg.)
Compilation Book
| Dordrecht: Springer | 2013
32811 Endnote
Editor(s)
Gurevych, Iryna; Kim, Jungi
Title:
The people's web meets NLP. Collaboratively Constructed Language Resources
Published:
Dordrecht: Springer, 2013 (Theory and applications of natural language processing)
DOI:
10.1007/978-3-642-35085-6
URL:
https://link.springer.com/book/10.1007/978-3-642-35085-6
Publication Type:
2. Herausgeberschaft; Sammelband (keine besondere Kategorie)
Language:
Englisch
Keywords:
Automatisierung; Computerlinguistik; Computerspiel; Data Mining; Forschung; Gemeinschaft; Indexierung; Kooperation; Mehrsprachigkeit; Methodologie; Nachschlagewerk; Ontologie; Schreiben; Semantic Web; Soziale Software; Sprachanalyse; Sprache; Textanalyse; Textverarbeitung; Wissen; World wide web 2.0
Abstract (english):
The application of collective intelligence in the domain of language yielded collaboratively constructed language resources (CCLR) that can be used in a variety of ways. For example, Wikipedia, Wiktionary, and other language resources constructed through crowdsourcing such as Games with a Purpose and Mechanical Turk have been used in many ways in NLP. Researchers started using such resources to substitute for or supplement conventional lexical semantic resources such as WordNet or linguistically annotated corpora in different NLP tasks. Another research direction is to utilize NLP techniques to enhance the collaboration process and its outcome. Overall the emergence of CCLRs has generated new challenges to the research field that are to be addressed in the present book. As the research field of CCLRs matures, it has become necessary to summarize a set of results to advance and focus the further research effort.
DIPF-Departments:
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