With the rapid development of satellite technology, remote sensing data has entered era big data, and intelligent processing image been paid more attention. Through semantic research ability is greatly improved. This paper aims to introduce analyze application progress from perspective semantic. Firstly, it introduces characteristics knowledge data; Secondly, concept, construction fields are in...

Semantic role labels are the representation of the grammatically relevant aspects of a sentence meaning. Capturing the nature and the number of semantic roles in a sentence is therefore fundamental to correctly describing the interface between grammar and meaning. In this paper, we compare two annotation schemes, PropBank and VerbNet, in a task-independent, general way, analysing how well they ...

Fast changing knowledge systems on the Internet can be accessed more efficiently with the help of automatic document summarization and updating techniques. The aim of multi-document update summary generation is to construct a summary unfolding the mainstream of data from a collection of documents based on the hypothesis that the user has already read a set of previous documents. In order to pro...

The workshop has been subsidized by the OntoWeb Consortium (www.ontoweb.org, EU Thematic Network on Semantic Web). We have received 15 papers in total. We had experts representing both the semantic web and the IR fields as reviewers. All the submitted papers were thoroughly reviewed by at least 4 people representing both fields. Based on these reviews, we selected 7 very good papers dealing wit...

As Extensible Markup Language (XML) is emerging as the data format of the In-ternet era, there are increasing needs to eeciently store and query XML data. One path to this goal is transforming XML data into relational format in order to use relational database technology. Although several transformation algorithms exist, they are incomplete in the sense that they focus only on structural aspect...

Understanding semantic similarity among images is the core of a wide range of computer graphics and computer vision applications. An important step towards this goal is to collect and learn human perceptions. Interestingly, the semantic context of images is often ambiguous as images can be perceived with emphasis on different aspects, which may be contradictory to each other. In this paper, we ...

With the popularity of model-driven methodologies, and the abundance of modelling languages, a major question for a requirements engineer is: which language is suitable for modelling a system under study? We address this question from a semantic point-of-view for big-step modelling languages (BSMLs). BSMLs are a popular class of behavioural modelling languages in which a model can respond to an...

In this paper we present the novel paradigm of Social Semantic Bookmarking. Social Semantic Bookmarking combines the positive aspects of semantic annotation with those of social bookmarking and tagging while avoiding their respective drawbacks like the cumbersome maintenance of ontologies or the lacking semantic precision of tags. Social semantic bookmarking tools allow for the annotation of in...

In this thesis proposal we present a novel semantic embedding method, which aims at consistently performing semantic clustering at sentence level. Taking into account special aspects of Vector Space Models (VSMs), we propose to learn reproducing kernels in classification tasks. By this way, capturing spectral features from data is possible. These features make it theoretically plausible to mode...

A number of semantic annotation efforts have produced a variety of annotated corpora, capturing various aspects of semantic knowledge in different formalisms. Due to to the cost of these annotation efforts and the relatively small amount of semantically annotated corpora, we argue it is advantageous to be able to leverage as much annotated data as possible. This work presents a preliminary expl...