MnM: Ontology Driven Semi-automatic and Automatic Support for Semantic Markup
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
SemTag and seeker: bootstrapping the semantic web via automated semantic annotation
WWW '03 Proceedings of the 12th international conference on World Wide Web
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Survey of semantic annotation platforms
Proceedings of the 2005 ACM symposium on Applied computing
An ontology engineering methodology for DOGMA
Applied Ontology - Ontological Foundations of Conceptual Modelling
On Constructing, Grouping and Using Topical Ontology for Semantic Matching
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
Integrating keywords and semantics on document annotation and search
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
DIY-CDR: an ontology-based, Do-It-Yourself component discoverer and recommender
Personal and Ubiquitous Computing
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In a Do-It-Yourself software assemblage environment, it is important for the amateurs and technicians to find the right building blocks before assembling their own solutions. We have designed an ontology-based do-it-yourself architecture, which assists users to find suitable components and guide them to the assemblage. In particular, a tool called DIY-CDR (Do-It-Yourself Component Discover and Recommender) has been designed and implemented. The matching engine in DIY-CDR uses domain ontologies and annotation sets of the components and compares users' requirements to the annotation sets. Since the components contain little metadata information and their descriptions are often free texts, how to automatically annotate these components becomes a problem. In this paper, we propose a solution called Onto-Ann, which is an automatic and semantically rich annotation tool. It uses combined technologies from natural language processing (NLP), social study and ontology.