Automatic Report Generation from Ontologies: The MIAKT Approach

Bontcheva, Kalina; Wilks, Yorick

doi:10.1007/978-3-540-27779-8_28

Cited by 63 publications

(52 citation statements)

References 7 publications

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“…The advantages of Wilcock's approach [12,11] is that it is fully automatic and does not require a lexicon. A more recent system which generates reports from RDF and DAML ontologies is MIAKT [3]. In contrast to Wilcock's approach, MIAKT [3] requires some manual input (lexicons and domain schemas), but on the other hand it generates more fluent reports, oriented towards end-users, not ontology builders.…”

Section: Introductionmentioning

confidence: 99%

“…A more recent system which generates reports from RDF and DAML ontologies is MIAKT [3]. In contrast to Wilcock's approach, MIAKT [3] requires some manual input (lexicons and domain schemas), but on the other hand it generates more fluent reports, oriented towards end-users, not ontology builders. It also uses reasoning and the property hierarchy to avoid repetitions, enable more generic text schemas, and perform aggregation.…”

Section: Introductionmentioning

confidence: 99%

“…Systems like Wilcock's [11] and MIAKT [3] tend to adopt simpler approaches, exploring generalities in the domain ontology, because their goal is to lower the effort for customising the system to new domains. Sophisticated systems, while offering more flexibility and expressiveness, are difficult to adapt by non-NLG experts.…”

Section: Introductionmentioning

confidence: 99%

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Generating Tailored Textual Summaries from Ontologies

Bontcheva

2005

Lecture Notes in Computer Science

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Abstract. This paper presents the ONTOSUM system which uses Natural Language Generation (NLG) techniques to produce textual summaries from Semantic Web ontologies. The main contribution of this work is in showing how existing NLG tools can be adapted to Semantic Web ontologies, in a way which minimises the customisation effort while offering more diverse output than template-based ontology verbalisers. A novel dimension of this work is the focus on tailoring the summary formatting and length according to a device profile (e.g., mobile phone, Web browser). Another innovative idea is the use of ontology mapping for summary generation from different ontologies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Generating Tailored Textual Summaries from Ontologies

Bontcheva

2005

Lecture Notes in Computer Science

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“…Current efforts in NLG have two main focuses. The first one is to provide tools specific oriented to semantic web platforms, and the second one is to design NLG systems that keep the system simple enough to be maintained by non-NLG experts, but without losing quality of the text output ( [32], [33], [34], and [35]). Since I expect that most of the users will not be NLG experts, these proposals can be very useful for the Semantic Web.…”

Section: Knowledge Visualization and Natural Language Generation (Nlg)mentioning

confidence: 99%

“…To facilitate the understanding of the information showed by the graphical interface, I decided to integrate ONTOSUM [35], a generator for textual tailored summaries from ontologies. I chose ONTOSUM because is based on a well tested technology [32], it is domain-independent, it is designed for non-NLG experts, and it supports entries in different formal ontology languages like RDF(S), DAML+OIL and OWL.…”

Section: Knowledge Visualizationmentioning

confidence: 99%

Towards Cspaces: A New Perspective for the Semantic Web

Martín-Recuerda

Industrial Applications of Semantic Web

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Abstract:Information overload is mainly the result of the combination of four factors: the enormous amount of information available; the heterogeneity of information sources and information channels; the generation of a significant percentage of redundant information; and inefficient mechanisms for filtering, searching and classifying information. Given that the former factor cannot be changed, and current forecast expects that information grows exponentially in the next years, research and industry efforts are focusing to overcome the other three. The association of machine-understandable semantics to formally describe data published on the Web and the development of appropriate tools that can handle this method to describe data are the approaches that the promoters of the Semantic Web have suggested to overcome the problem of information overload in the Web. Although, the Semantic Web promises a new level of service with regard to the current Web, a more drastic approach is required. Conceptual Spaces (CSpaces) envision the future of the Semantic Web as a cooperative environment where communication between humans, machines, and human-and-machines will be reduced to the acts of publishing and reading machine processable semantics in a persistent collection of individual and shared information spaces. Decreasing the amount of syntactic data representation in the Semantic Web, and therefore, make machine processable semantics the prevalent representation formalism will facilitate interoperation between heterogeneous applications, web services, agents, humans and so on. Natural language generation and graphical knowledge visualization techniques will make possible that humans deal with this "purest semantic" Web. In addition, CSpaces will also decrease redundancy of the information stored and will provide a better organization of the data articulated around ontologies.

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The Semantic Web as a Linguistic Resource: Opportunities for Natural Language Generation

Mellish

Sun

2006

Research and Development in Intelligent Systems XXII

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Automatic Report Generation from Ontologies: The MIAKT Approach

Cited by 63 publications

References 7 publications

Generating Tailored Textual Summaries from Ontologies

Generating Tailored Textual Summaries from Ontologies

Towards Cspaces: A New Perspective for the Semantic Web

The Semantic Web as a Linguistic Resource: Opportunities for Natural Language Generation

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