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A Protégé Plug-In for Ontology Extraction from Text Based on Linguistic Analysis [chapter]

Paul Buitelaar, Daniel Olejnik, Michael Sintek
2004 Lecture Notes in Computer Science  
abstracts. 1 See for instance the overview of ontology learning systems and approaches in OntoWeb deliverable 1.5 (Gomez-Perez et al., 2003).  ...  to concept and attribute candidates (i.e.  ...  Special thanks also to our colleagues at Saarland University (Thierry Declerck, Mihaela Hutanu, Alexander Schutz) for making available the SCHUG linguistic analysis tool and for their cooperation in the  ... 
doi:10.1007/978-3-540-25956-5_3 fatcat:sjxltbk2knawncq4m2gqzemldq

A Semi-automatic Method to Ontology Design by Using FCA

Hele-Mai Haav
2004 International Conference on Concept Lattices and their Applications  
Ontology designer is given this initial ontology expression for further extension by adding concepts and relationships (part-of, related to, etc) by using a rule language based on Horn clauses.  ...  This paper presents a semi-automatic method for ontology extraction and design. The method is based on Formal Concept Analysis and a Horn clause model of a concept lattice.  ...  Our approach provides tools for automatic or semi-automatic extraction of taxonomy of concepts from domain-specific texts, automatic transformation this initial ontology to Horn clause language and a rule  ... 
dblp:conf/cla/Haav04 fatcat:tdzq2mtxqrfqrc26zsnyxvibdq

Learning Rules for Semantic Video Event Annotation [chapter]

Marco Bertini, Alberto Del Bimbo, Giuseppe Serra
2008 Lecture Notes in Computer Science  
In this paper we present a framework for semantic video event annotation that exploits an ontology model, referred to as Pictorially Enriched Ontology, and ontology reasoning based on rules.  ...  In our approach we propose an adaptation of the First Order Inductive Learner (FOIL) technique to the Semantic Web Rule Language (SWRL) standard to learn rules.  ...  This approach permits to create an ontology structure that allows to perform automatic semantic annotation of video sequences matching visual descriptors and recognizing events described using automatically  ... 
doi:10.1007/978-3-540-85891-1_22 fatcat:agszriecg5axdj73ohgowvj4uq

Video Annotation and Retrieval Using Ontologies and Rule Learning

Lamberto Ballan, Marco Bertini, Alberto Del Bimbo, Giuseppe Serra
2010 IEEE Multimedia  
Acknowledgment This work is partially supported by the European Information Society Technologies Vidi-Video Project (contract FP6-045547) and the IM3I Project (contract FP7-222267).  ...  In this article, we present an approach for automatic annotation and retrieval of video content based on ontologies and semanticconcept classifiers.  ...  Automatic rule learning with first-order logic In our approach, first-order logic rules defined in SWRL are automatically learned from the knowledge that is embedded in the ontology.  ... 
doi:10.1109/mmul.2010.4 fatcat:fane36qih5aehlodmqaqetcdma

Querying Semantic Web Resources Using TRIPLE Views [chapter]

Zoltán Miklós, Gustaf Neumann, Uwe Zdun, Michael Sintek
2003 Lecture Notes in Computer Science  
We present an approach based on multiple views expressed in ontologies simpler than the domain ontology.  ...  We present our approach with examples from the e-learning domain using the Semantic Web query and transformation language TRIPLE.  ...  Acknowledgement This work was supported by the Elena project and is partly sponsored by the European Commission (IST-2001-37264).  ... 
doi:10.1007/978-3-540-39718-2_33 fatcat:vhorlxjj7fephl2ils7e4uiaoq

Towards Machine Learning on the Semantic Web [chapter]

Volker Tresp, Markus Bundschus, Achim Rettinger, Yi Huang
2008 Lecture Notes in Computer Science  
Within a broad range of possible applications machine learning will play an increasingly important role: Machine learning solutions have been developed to support the management of ontologies, for the  ...  semi-automatic annotation of unstructured data, and to integrate semantic information into web mining.  ...  We thank Frank Harmelen, and two anonymous reviewers for their valuable comments.  ... 
doi:10.1007/978-3-540-89765-1_17 fatcat:ixm5kgibajgmvohdfffo43cijm

Populating the Semantic Web by Macro-reading Internet Text [chapter]

Tom M. Mitchell, Justin Betteridge, Andrew Carlson, Estevam Hruschka, Richard Wang
2009 Lecture Notes in Computer Science  
A second approach is to take advantage of pre-existing databases, and to develop common ontologies, publishing standards, and reward systems to make this data widely accessible.  ...  We also describe preliminary results demonstrating that machine learning algorithms can learn to extract tens of thousands of facts to populate a diverse ontology, with imperfect but reasonably good accuracy  ...  This research has been supported by DARPA, Google, and the Brazilian Research Agency CAPES. Yahoo! Inc. has provided graduate fellowship support as well as access to their M45 computing cluster.  ... 
doi:10.1007/978-3-642-04930-9_66 fatcat:vzu27ue3sncddbj47arc7ldlcu

A Formalization of Ontology Learning From Text

Michael Sintek, Paul Buitelaar, Daniel Olejnik
2004 Workshop on Evaluation of Ontology-based Tools  
Recent developments towards knowledge-based applications in general and Semantic Web applications in particular are leading to an increased interest in ontologies and in dynamic methods for developing  ...  Such methods mostly combine a certain level of linguistic analysis with statistical and/or machine learning approaches to find potentially interesting concepts and relations between them.  ...  Acknowledgements This research has in part been supported by EC grants IST-2000-29243 for the OntoWeb project and IST-2000-25045 for the MEMPHIS project, and by bmb+f grant 01 IMD01 A for the SmartWeb  ... 
dblp:conf/eon/SintekBO04 fatcat:447zuew5xjfmnbjuliwkz6vcb4

Extraction of Genic Interactions with the Recursive Logical Theory of an Ontology [chapter]

Alain-Pierre Manine, Erick Alphonse, Philippe Bessières
2010 Lecture Notes in Computer Science  
In this context, automatically acquiring the resources of an IE system becomes an ontology learning task: terms, synonyms, conceptual hierarchy, relational hierarchy, and the logical theory of the ontology  ...  We validate our approach by using a relational learning algorithm, which handles recursion, to learn a recursive logical theory from a text corpus on the bacterium Bacillus subtilis.  ...  We propose an integrated approach to address these three points, in which the logical theory of an ontology generalises regular IE patterns and is responsible for the extraction.  ... 
doi:10.1007/978-3-642-12116-6_47 fatcat:dr7ztzsz3nfk3hgokrboied7pq

Inductive Learning of the Surgical Workflow Model through Video Annotations

Hirenkumar Nakawala, Elena de Momi, Laura Erica Pescatori, Anna Morelli, Giancarlo Ferrigno
2017 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)  
The algorithm was able to learn 18 rules for surgical workflow model with 0.88 precision, and 0.94 F1 score on the standard video annotation data, representing entities of the surgical workflow, which  ...  Rule-based surgical workflows have shown to be useful to create context-aware systems. However, manually constructing production rules is a time-intensive and laborious task.  ...  Each Horn-clause defines some relations given a set of examples belonging to the relations and a set of examples not belonging to the relations.  ... 
doi:10.1109/cbms.2017.91 dblp:conf/cbms/NakawalaMPMF17 fatcat:a2gro3r3mffdvkn2piuheqvgz4

Learning to construct knowledge bases from the World Wide Web

Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom Mitchell, Kamal Nigam, Seán Slattery
2000 Artificial Intelligence  
The first is an ontology that defines the classes (e.g., company, person, employee, product) and relations (e.g., employed_by, produced_by) of interest when creating the knowledge base.  ...  This article describes our general approach, several machine learning algorithms for this task, and promising initial results with a prototype system that has created a knowledge base describing university  ...  If a page is determined to be a class member, an entity representing that page is placed into the knowledge base, and the ontology relations for that page are instantiated based on learned rules and the  ... 
doi:10.1016/s0004-3702(00)00004-7 fatcat:h4i7yzy4izadpknsd4qpanhh3y

Bootstrapping an Ontology-Based Information Extraction System [chapter]

Alexander Maedche, Günter Neumann, Steffen Staab
2003 Studies in Fuzziness and Soft Computing  
In this paper we present a bootstrapping approach that allows for the fast creation of an ontology-based information extracting system relying on several basic components, viz. a core information extraction  ...  system, an ontology engineering environment and an inference engine.  ...  The research presented in this paper has been partially funded by BMBF under grant number 01IN802 (project "GETESS") and by US Air Force in the DARPA DAML project "OntoAgents" (01IN901C0).  ... 
doi:10.1007/978-3-7908-1772-0_21 fatcat:5euzi36esbcohgozw2nncldksu

Linguistic Patterns for Information Extraction in OntoCmaps

Amal Zouaq, Dragan Gasevic, Marek Hatala
2012 International Semantic Web Conference  
Our experimental results show that these patterns are a good starting base for text mining initiatives in general and ontology learning in particular.  ...  This paper presents a number of syntactic patterns, based on dependency grammars, which output triples useful for the ontology learning task.  ...  There have been several attempts to use LSPs for ontology learning [2, 3, 6, 7] , relation extraction [7] or for axiom extraction [3] .  ... 
dblp:conf/semweb/ZouaqGH12 fatcat:gitw7a4fsvbg7lmk2uiumpdjgm

CaVa: An Example of the Automatic Generation of Virtual Learning Spaces [chapter]

Ricardo G. Martini, Cristiana Araújo, Pedro Rangel Henriques, Maria João Varanda Pereira
2018 Advances in Intelligent Systems and Computing  
In this paper, a system to automatically construct those learning spaces based on a digital repository is presented.  ...  The system takes XML files from repositories and populates an ontology (representing the knowledge base, the core of our system) to create the triples internal representation.  ...  Architecture of the System The core, or heart, of this approach is an ontology that models the knowledge domain related to the museum to be built.  ... 
doi:10.1007/978-3-319-77703-0_63 fatcat:74rslij7pnfibd3n44xim5cwj4

Database to Semantic Web Mapping Using RDF Query Languages [chapter]

Cristian Pérez de Laborda, Stefan Conrad
2006 Lecture Notes in Computer Science  
In this paper, we present an approach to map legacy data stored in relational databases into the Semantic Web using virtually any modern RDF query language, as long as it is closed within RDF.  ...  Consequently, a Semantic Web developer does not need to learn and adopt a new mapping language, but he may perform the mapping task using his preferred RDF query language.  ...  First, we introduce Relational.OWL, an approach to automatically transform relational data and schema items into a Semantic Web representation.  ... 
doi:10.1007/11901181_19 fatcat:lxqbwqau25hetbrr7vm7pxonoy
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