Document annotation and ontology population from linguistic extractions

Amardeilh, Florence; Laublet, Philippe; Minel, Jean-Luc

doi:10.1145/1088622.1088651

Cited by 26 publications

(23 citation statements)

References 8 publications

(5 reference statements)

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“…3. Systems like [3,13,17,25] which can extract complex instances (the three first systems consider only one level of aggregation), require a complete syntactic analysis. In some cases, a semantic and/or learning processing is also needed.…”

Section: Resultsmentioning

confidence: 99%

“…The system in [13] shows better results, but complete syntactic and semantic analyses are used, even for reconstructing instances with a few aggregation levels. Finally, [17] considers a very complex domain, uses complete syntactic and semantic analysis, and results both in precision and recall are lower. 4.…”

Section: Resultsmentioning

confidence: 99%

“…Regarding the nature of the extracted information, only a few methods [3,9,17] deal with aggregated instances and relations between entities. However, discovered entity associations only involve one aggregation level, that is, they do not attempt to find entity compositions through relationship chains, logic constructors (e.g.…”

Section: Related Researchmentioning

confidence: 99%

See 2 more Smart Citations

Generating complex ontology instances from documents

Dánger¹,

Berlanga²

2009

Journal of Algorithms

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Generating complex ontology instances from documents

Dánger¹,

Berlanga²

2009

Journal of Algorithms

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“…Ontology population from linguistic extractions is also the main focus of [13]. Knowledge acquisition rules are used to map concept tree nodes to ontology instances.…”

Section: Related Workmentioning

confidence: 99%

Semantic Content Access Using Domain-Independent NLP Ontologies

Witte

Krestel

2010

Natural Language Processing and Information Systems

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Abstract. We present a lightweight, user-centred approach for document navigation and analysis that is based on an ontology of text mining results. This allows us to bring the result of existing text mining pipelines directly to end users. Our approach is domain-independent and relies on existing NLP analysis tasks such as automatic multi-document summarization, clustering, question-answering, and opinion mining. Users can interactively trigger semantic processing services for tasks such as analyzing product reviews, daily news, or other document sets.

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“…Ageneral approach of ontology-based information extraction is provided by GATE [BTMC04] which is as ubcomponent of our prototype which is described technically in [AD08]. In [ALM05], the authors presented away to extract information from text for ontology population, that we adopted. We base the knowledge worker'sPKS on the Semantic Desktop [SBD05] and his applications in PIM [SGRB08].…”

Section: R Elated Workmentioning

confidence: 99%

Professional Knowledge Management

Althoff¹,

Dengel²,

Bergmann³

et al. 2005

Lecture Notes in Computer Science

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publishes this series in order to make available to a broad public recent findings in informatics (i.e. computer science and information systems), to document conferences that are organized in cooperation with GI and to publish the annual GI Award dissertation.Broken down into the fields of • Seminar • Proceedings • Dissertations • Thematics current topics are dealt with from the fields of research and development, teaching and further training in theory and practice. The Editorial Committee uses an intensive review process in order to ensure the high level of the contributions.The volumes are published in German or English.Information: http://www.gi-ev.de/service/publikationen/lni/ The WM2009 is the 5th conference of the bi-annual series "Professional Knowledge Management". A broad integrative overview on currents trends and new insights in organisational, social and technical aspects of knowledge management are provided to participants from academia and practice. The conference programme is composed of 11 Workshops, invited talks, tutorials, a poster and demo session and an exhibition. It also provides space to discuss problems and challenges, share experiences and for networking. This volume contains refereed contributions from the workshops. 145ISSN 1617-5468 ISBN 978-3-88579-239-0 PrefaceKnowledge has become more and more an imperative key success factor for each company. It plays a key role in many business processes, in product development and advanced customer satisfaction. This is particularly important as products are becoming more complex and processesm ore knowledge-intensive. Many companies are going to realize their knowledge potential and improve their knowledge management. New technologies like those known under the "Web2.0" label and new methods like intellectual capital statements support the improvement of knowledge management.The 5 th conference on Professional Knowledge Management provides a broad integrative overview of organizational,c ultural, social and technical aspects on knowledge management. Focus of the conference is bringing together different research disciplines and sharing experiences gained in the different areas where knowledge management is being applied. In particular the 5 th conference on Professional Knowledge Management consists of five tutorials and eleven workshops focusingo n current trends. Topics of these tutorials andworkshops include knowledge services and mashups, knowledge and social networks, convergence of knowledge management and e-learning, productive knowledge work, personal knowledge management, experience management, measuring and benchmarking the economical success of knowledge management, integrating knowledge base systems as well as knowledge management approaches specialised for SME, for companies from the financial sector, or for combination with enterprise communication.Ninety-five contributions were submitted to the workshops of which 45 were accepted as long papers and 20 as short paper. These 65 contributions are collected in this proceedin...

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Document annotation and ontology population from linguistic extractions

Cited by 26 publications

References 8 publications

Generating complex ontology instances from documents

Generating complex ontology instances from documents

Semantic Content Access Using Domain-Independent NLP Ontologies

Professional Knowledge Management

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