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73
Efficient content creation on the semantic web using metadata schemas with domain ontology services (System description)
- IN: PROCEEDINGS OF THE EUROPEAN SEMANTIC WEB CONFERENCE ESWC 2007
, 2007
"... Metadata creation is one of the major challenges in developing the Semantic Web. This paper discusses how to make provision of metadata easier and costeffective by an annotation editor combined with shared ontology services. We have developed an annotation system supporting distributed collaboration ..."
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Cited by 22 (12 self)
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Metadata creation is one of the major challenges in developing the Semantic Web. This paper discusses how to make provision of metadata easier and costeffective by an annotation editor combined with shared ontology services. We have developed an annotation system supporting distributed collaboration in creating annotations, and hiding the complexity of the annotation schema and the domain ontologies from the annotators. Our system adapts flexibly to different metadata schemas, which makes it suitable for different applications. Support for using ontologies is based on ontology services, such as concept searching and browsing, concept URI fetching, semantic autocompletion and linguistic concept extraction. The system is being tested in various practical semantic portal projects.
A.: HarVANA - Harvesting Community Tags to Enrich Collection Metadata
- 16 – 20, pp 147
"... Collaborative, social tagging and annotation systems have exploded on the Internet as part of the Web 2.0 phenomenon. Systems such as Flickr, Del.icio.us, Technorati, Connotea and LibraryThing, provide a community-driven approach to classifying information and resources on the Web, so that they can ..."
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Cited by 21 (1 self)
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Collaborative, social tagging and annotation systems have exploded on the Internet as part of the Web 2.0 phenomenon. Systems such as Flickr, Del.icio.us, Technorati, Connotea and LibraryThing, provide a community-driven approach to classifying information and resources on the Web, so that they can be browsed, discovered and re-used. Although social tagging sites provide simple, user-relevant tags, there are issues associated with the quality of the metadata and the scalability compared with conventional indexing systems. In this paper we propose a hybrid approach that enables authoritative metadata generated by traditional cataloguing methods to be merged with community annotations and tags. The HarvANA (Harvesting and Aggregating Networked Annotations) system uses a standardized but extensible RDF model for representing the annotations/tags and OAI-PMH to harvest the annotations/tags from distributed community servers. The harvested annotations are aggregated with the authoritative metadata in a centralized metadata store. This streamlined, interoperable, scalable approach enables libraries, archives and repositories to leverage community enthusiasm for tagging and annotation, augment their metadata and enhance their discovery services. This paper describes the HarvANA system and its evaluation through a collaborative testbed with the National Library of Australia using architectural images from PictureAustralia.
Unsupervised information extraction from unstructured, ungrammatical data sources on the world wide web
- International Journal of Document Analysis and Recognition (IJDAR), Special Issue on Noisy Text Analytics
, 2007
"... Abstract Information extraction from unstructured, ungrammatical data such as classified listings is difficult because traditional structural and grammatical extraction methods do not apply. Previous work has exploited reference sets to aid such extraction, but it did so using supervised machine lea ..."
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Cited by 15 (4 self)
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Abstract Information extraction from unstructured, ungrammatical data such as classified listings is difficult because traditional structural and grammatical extraction methods do not apply. Previous work has exploited reference sets to aid such extraction, but it did so using supervised machine learning. In this paper, we present an unsupervised approach that both selects the relevant reference set(s) automatically and then uses it for unsupervised extraction. We validate our approach with experimental results that show our unsupervised extraction is competitive with supervised machine learning approaches, including the previous supervised approach that exploits reference sets.
Ontology Enrichment Through Automatic Semantic Annotation of On-Line Glossaries
"... Abstract. The contribution of this paper is to provide a methodology for automatic ontology enrichment and for document annotation with the concepts and properties of a domain core ontology. Natural language definitions of available glossaries in a given domain are parsed and converted into formal ( ..."
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Cited by 11 (0 self)
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Abstract. The contribution of this paper is to provide a methodology for automatic ontology enrichment and for document annotation with the concepts and properties of a domain core ontology. Natural language definitions of available glossaries in a given domain are parsed and converted into formal (OWL) definitions, compliant with the core ontology property specifications. To evaluate the methodology, we annotated and formalized a relevant fragment of the AAT glossary of art and architecture, using a subset of 10 properties defined in the CRM CIDOC cultural heritage core ontology, a recent W3C standard. Keywords: Ontology Learning, Core Ontology, Glossaries.
A browser-based tool for collaborative distributed annotation for the semantic web
- September 26 2006) 5th International Semantic Web Conference, Semantic Authoring and Annotation Workshop
, 2006
"... This paper presents a prototype of an ontology-based semantic annotation tool Saha. The tool eases the process of creating ontological descriptions of documents by providing a simple user interface that hides the complexity of ontologies from annotators. Saha is used with a web browser, and it suppo ..."
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Cited by 10 (6 self)
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This paper presents a prototype of an ontology-based semantic annotation tool Saha. The tool eases the process of creating ontological descriptions of documents by providing a simple user interface that hides the complexity of ontologies from annotators. Saha is used with a web browser, and it supports collaborative distributed creation of metadata by centrally storing annotations, which can be viewed and edited by different annotators. Concepts defined in external ontologies can be imported and used in annotations by connecting Saha to ontology servers. The tool is being tested in practical semantic portal projects. Categories and Subject Descriptors H.3.1 [Information storage and retrieval]: Content Analysis
Growing Triples on Trees: an XML-RDF Hybrid Model for Annotated Documents
"... Content on today’s Web is typically document-structured and richly connected; XML is by now widely adopted to represent Web data. Moreover, the vision of a computerunderstandable Web relies on Web (and real world) resources described by simple properties having names or values; URIs are the normativ ..."
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Cited by 8 (5 self)
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Content on today’s Web is typically document-structured and richly connected; XML is by now widely adopted to represent Web data. Moreover, the vision of a computerunderstandable Web relies on Web (and real world) resources described by simple properties having names or values; URIs are the normative method of identifying resources and RDF (the Resource Description Framework) enjoys important traction as a way to encode such statements. We present XR, a carefully designed hybrid model between XML and RDF, for describing RDF-annotated XML documents. XR follows and combines the W3C’s XML, URI and RDF standards by assigning URIs to all XML nodes and enabling these URIs to appear in RDF statements. The XR management platform thus provides the capabilities to create and handle interconnected XML and RDF content. We define the XR data model, its query language, and present preliminary results with a prototype implementation. 1.
H.: Annotation of enterprise models for interoperability purposes
- In: IEEE International Workshop on Advanced Information Systems for Enterprises, IWAISE’2008
, 2008
"... The purpose of annotations is to describe the content of “something ” and they may be considered as meta-data. They are used for a while for text books, articles, hypertext documents and so on. We explore their usage in semantic-based and modelbased interoperability, with the aim to make explicit th ..."
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Cited by 7 (1 self)
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The purpose of annotations is to describe the content of “something ” and they may be considered as meta-data. They are used for a while for text books, articles, hypertext documents and so on. We explore their usage in semantic-based and modelbased interoperability, with the aim to make explicit the meaning and the structure of given models (artefacts) to enable not only their understanding, but also their exchange (and their possible transformation) between collaborating actors (human or machine). We propose categories and types of annotations helpful to explicit the deep meaning of models and to ease their exchange. 1.
Integrating keywords and semantics on document annotation and search
- In Proceedings of the International Conference on On the Move to Meaningful Internet Systems: Bahareh R. Heravi 193 Part II (OTM'10), Meersman
, 2010
"... Abstract. This paper describes GoNTogle, a framework for document annotation and retrieval, built on top of Semantic Web and IR technologies. GoNTogle supports ontology-based annotation for documents of several formats, in a fully collaborative environment. It provides both manual and automatic anno ..."
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Cited by 6 (0 self)
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Abstract. This paper describes GoNTogle, a framework for document annotation and retrieval, built on top of Semantic Web and IR technologies. GoNTogle supports ontology-based annotation for documents of several formats, in a fully collaborative environment. It provides both manual and automatic annotation mechanisms. Automatic annotation is based on a learning method that exploits user annotation history and textual information to automatically suggest annotations for new documents. GoNTogle also provides search facilities beyond the traditional keyword-based search. A flexible combination of keyword-based and semantic-based search over documents is proposed in conjunction with advanced ontology-based search operations. The proposed methods are implemented in a fully functional tool and their effectiveness is experimentally validated.
Ontology based annotation of text segments
- In proceedings of the 22 nd Annual ACM Symposium on Applied Computing, 2007
"... This work exploits the logical structure of information rich texts to automatically annotate text segments contained within them using a domain ontology. The underlying assumption behind this work is that segments in such documents embody self contained informative units. Another assumption is that ..."
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Cited by 5 (3 self)
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This work exploits the logical structure of information rich texts to automatically annotate text segments contained within them using a domain ontology. The underlying assumption behind this work is that segments in such documents embody self contained informative units. Another assumption is that segment headings coupled with a document’s hierarchical structure offer informal representations of segment content; and that matching segment headings to concepts in an ontology/thesaurus can result in the creation of formal labels/meta-data for these segments. When an encountered heading can not be matched with any concepts in the ontology, the hierarchical structure of the document is used to infer where a new concept represented by this heading should be added in the ontology. So, in this work the bootstrap ontology is also enriched by new concepts encountered within input documents. This paper also presents issues/problems related to matching textual entities to concepts in an incomplete ontology. The approach presented in this paper was applied to a set of agricultural extension documents. The results of carrying out this experiment demonstrates that the proposed approach is capable of automatically annotating segments with concepts that describe a segment’s content with a high degree of accuracy.
Enhancing Semantic Web Data Access
, 2006
"... The Semantic Web was invented by Tim Berners-Lee in 1998 as a web of data for machine consumption. Its applicability in supporting real world applications on the World Wide Web, however, remains unclear to this day because most existing works treat the Semantic Web as one universal RDF graph and ign ..."
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Cited by 4 (3 self)
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The Semantic Web was invented by Tim Berners-Lee in 1998 as a web of data for machine consumption. Its applicability in supporting real world applications on the World Wide Web, however, remains unclear to this day because most existing works treat the Semantic Web as one universal RDF graph and ignore the Web aspect. In fact, the Semantic Web is distributed on the Web as a web of belief: each piece of Semantic Web data is independently published on the Web as a certain agent’s belief instead of the universal truth. Therefore, we enhance the current conceptual model of the Semantic Web to characterize both the content and the context of Semantic Web data. A significant sample dataset is harvested to demonstrate the non-trivial presence and the global properties of the Semantic Web on the Web. Based on the enhanced conceptual model, we introduce a novel search and navigation model for the unique behaviors in Web-scale Semantic Web data access, and develop an enabling tool – the Swoogle Semantic Web search engine. To evaluate the data quality of Semantic Web data, we also (i) develop an explainable ranking schema that orders the popularity of Semantic Web documents and terms, and (ii) introduce a new level of granularity of Semantic Web data – RDF molecule that supports lossless RDF graph decomposition and effective provenance tracking. This dissertation systematically investigates the Web aspect of the Semantic Web. Its primary contribu-tions are the enhanced conceptual model of the Semantic Web, the novel Semantic Web search and navigation model, and the Swoogle Semantic Web search engine.