For intelligent robotics applications, extending 3D mapping to 3D semantic mapping enables robots to, not only localize themselves with respect to the scene’s geometrical features but also simultaneously understand the higher level meaning of the scene contexts. Most previous methods focus on geometric 3D reconstruction and scene understanding independently notwithstanding the fact that joint e...

A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360◦. The matching is based on sema...

Latent semantic mapping (LSM) is a generalization of latent semantic analysis (LSA), a paradigm originally developed to capture hidden word patterns in a text document corpus. In information retrieval, LSA enables retrieval on the basis of conceptual content, instead of merely matching words between queries and documents. It operates under the assumption that there is some latent semantic struc...

This paper introduces a novel wrapper-mediator based semantic data grid service mechanism to solve the problem of Semantic heterogeneity and few compatible data sources. It uses ontology based semantic information to wrap the heterogeneous data source, and employs mediator structure to supply accessing interface for the data sources, and it extends semantic query, mapping and fusion languages t...

The SWHi (Semantic Web for History) project is aimed at integrating, combining, and deducing information on the early American history, based on the Early American Imprints, Series I: Evans, 1639-1800 collection, to assist general users or historians in exploring American history by using new technology offered by the Semantic Web. What are the possibilities of Semantic Web technologies for org...

This paper presents shallow semantic parsing based only on HPSG parses. An HPSG-FrameNet map was constructed from a semantically annotated corpus, and semantic parsing was performed by mapping HPSG dependencies to FrameNet relations. The semantic parsing was evaluated in a Senseval-3 task; the results suggested that there is a high contribution of syntactic information to semantic analysis.

Ontology Mapping is a mandatory requirement for enabling semantic interoperability among different agents and services relying on different ontologies. This aspect becomes more critical in Peer-to-Peer (P2P) networks for several reasons: (i) the number of different ontologies can dramatically increase; (ii) mappings among peer ontologies have to be discovered on the fly and only on the parts of...

DBpedia is one of the very well known live projects from the Semantic Web. It is like a mirror version of the Wikipedia site in Semantic Web. Initially it publishes the information collected from the Wikipedia, but only that part which is relevant to the Semantic Web. Collecting information for Semantic Web from the Wikipedia is demonstrated as the extraction of structured data. DBpedia normall...

In the last decade, ontologies have played a key technology role for information sharing and agents interoperability in different application domains. In semantic web domain, ontologies are efficiently used to face the great challenge of representing the semantics of data, in order to bring the actual web to its full power and hence, achieve its objective. However, using ontologies as common an...

We describe a two-layer architecture for supporting semantic interpretation and domain reasoning in dialogue systems. Building systems that support both semantic interpretation and domain reasoning in a transparent and well-integrated manner is an unresolved problem because of the diverging requirements of the semantic representations used in contextual interpretation versus the knowledge repre...