As Sensor Network is used more and more widely in all fields, a large number of heterogeneous data is produced. In order to eliminate the heterogeneity and make these data shared and integrated semantically, semantic web technology is introduced in the sensor network. In this paper, we present a comprehensive review studies about Semantic Sensor Web (SSW) from the perspective of ontology, mappi...

This paper presents a framework based on ontologies, rules and mathematical semantic representation standards, for the automatic calculation of the level of quality of service perceived by the customers in telematic services. This automation is achieved by representing and using the mappings between technical quality of service and quality of experience in a knowledge-based framework supported ...

Semantic clustering is important to various fields in the modern information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a...

The Semantic Web aims at evolving the ‘web of data’ to an ‘intelligent information space’ which is responsive to both human beings and computer systems. Consequently, semantic technologies have emerged in many application fields, primarily to provide intelligent IT systems. Semantics, therefore, is considered to be the essence of systemic intelligence. In this paper, we introduce a lifecycle mo...

Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently large receptive fields is non trivial. This is even more so, when objects or classes present in an image significantly vary in size. Dilated convolutions have proven valuable for semantic segmentation, because they a...

In this paper we investigate social tags as a novel highvolume source of semantic metadata for music, using techniques from the fields of information retrieval and multivariate data analysis. We show that, despite the ad hoc and informal language of tagging, tags define a low-dimensional semantic space that is extremely well-behaved at the track level, in particular being highly organised by ar...

Classifying what-type questions into proper semantic categories is found more challenging than classifying other types in question answering systems. In this paper, we propose to classify what-type questions by head noun tagging. The approach highlights the role of head nouns as the category discriminator of whattype questions. To reduce the semantic ambiguities of head noun, we integrate local...

The paper reports on the results of an exploratory study into the topical organisation and stylistic features of argumentation in a corpus of ophthalmic clinical research papers. The study responds to the need for systematised and generalisable argumentation models in knowledgeintensive fields. We present here a schematised superstructure of the arguments from the corpus, charting the configura...

The vision of the Semantic Web is that a vast store of online information “meaningful to computers will unleash a revolution of new possibilities”. Unfortunately, the vast majority of information on the Web is formatted to be easily read by human users, not computer applications. In order to make the vision of the Semantic Web a reality, tools for automatically annotating Web content with seman...

The aim of the project is to construct classifiers which should assign semantic patterns to six given verbs, as accurately as possible. Each verb has a set of usual usage patterns (based on the Pattern Dictionary of English Verbs), defined by its semantic and syntactic characteristics. It is assumed that if we are able to automatically assign these patterns, it will help us in the general probl...