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1
Under consideration for publication in Theory and Practice of Logic Programming 1 A Probabilistic Logic Programming Event Calculus
In: http://users.iit.demokritos.gr/~a.artikis/publications/artikis-TPLP.pdf (2012)
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2
G.: Scalable semantic annotation of text using lexical and web resources
In: http://users.iit.demokritos.gr/~paliourg/papers/SETN2010.pdf (2010)
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3
A Name-Matching Algorithm for Supporting Ontology Enrichment
In: http://www.iit.demokritos.gr/~paliourg/papers/SETN2004a.pdf (2004)
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4
A Name-Matching Algorithm for Supporting Ontology Enrichment
In: http://www.samos.aegean.gr/samos_icsd/research/InCoSys/Publications/valarakosSetn04.pdf (2004)
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5
Enhancing ontological knowledge through ontology population and enrichment
In: http://users.iit.demokritos.gr/~alexv/publications/valarakosEKAW04.pdf (2004)
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6
Meta-learning beyond classification: A framework for information extraction from the Web
In: http://cgi.di.uoa.gr/~takis/atem03.pdf (2003)
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7
A Methodology for Enriching a Multi-Lingual Domain Ontology using
In: http://www.iit.demokritos.gr/~vangelis/papers/ICGL2003.pdf (2003)
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8
A Methodology for Enriching a Multi-Lingual Domain Ontology using Machine Learning
In: http://www.icsd.aegean.gr/incosys_old/publications/creteworkshop_ncsr.pdf (2003)
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9
A methodology for enriching a multi-lingual domain ontology using machine learning
In: https://labs-repos.iit.demokritos.gr/skel/crossmarc/external/publications/CreteWorkshop_NCSR.pdf (2003)
Abstract: Abstract. Ontologies accumulate and organize knowledge in a machine-processable and human-readable way providing a common understanding basis. Enriching a multi-lingual ontology is crucial for the success of many knowledge-based systems. We present an iterative ontology-driven methodology that enriches a multi-lingual domain ontology with new instances, exploiting machine learning techniques. The methodology is user-centered and aims to ease the task of ontology maintenance. Our first experiments show the strong dependency between the size of the initial ontology and the performance of the machine learning-based method. 1
URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.625.7509
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10
Using the Ellogon Natural Language Engineering Infrastructure
In: http://users.iit.demokritos.gr/~paliourg/papers/BCI2003.pdf (2003)
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11
Ellogon: A New Text Engineering Platform
In: http://www.iit.demokritos.gr/~paliourg/papers/LREC2002.ps.gz (2002)
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12
C.D.: Ellogon: A New Text Engineering Platform
In: http://www.lrec-conf.org/proceedings/lrec2002/pdf/211.pdf (2002)
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13
Ellogon: A new text engineering platform
In: http://users.iit.demokritos.gr/~paliourg/papers/LREC2002.pdf (2002)
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14
Role identification from free text using hidden Markov models
In: http://www.iit.demokritos.gr/~paliourg/papers/SETN2002.ps.gz (2002)
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15
Learning rules for large vocabulary word sense disambiguation,” in: T. Dean (Ed
In: http://users.iit.demokritos.gr/~paliourg/papers/IJCAI99.pdf (1999)
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16
Learning rules for large vocabulary word sense disambiguation,” in: T. Dean (Ed
In: http://ijcai.org/Past Proceedings/IJCAI-99 VOL-2/PDF/003.pdf (1999)
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17
KDTA: Automated Knowledge-Driven Text Annotation
In: http://www.db-net.aueb.gr/gbt/publications/PKDD2010_Papantoniou_etal.pdf
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18
Using the Ellogon Natural Language Engineering Infrastructure
In: http://www.iit.demokritos.gr/skel/bci03_workshop/papers/SESSION5_2-23_Petasis.pdf
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19
1Automatic adaptation of Proper Noun Dictionaries through cooperation of machine learning and probabilistic methods
In: http://wwwusers.di.uniroma1.it/~velardi/SIGIR2000.pdf
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20
Bootstrapping Ontology Evolution with Multimedia Information Extraction
In: http://users.iit.demokritos.gr/~paliourg/papers/BOEMIE2011a.pdf
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