An increasing number of biomedical resources provide their information on the Semantic Web and this creates the basis for a distributed knowledge base which has the potential to advance biomedical research [1]. This potential, however, cannot be realised until researchers from the life sciences can interact with information in the Semantic Web. In particular, there is a need for tools that prov...

Today malware is a serious threat to our society. Several researchers are studying detection and mitigation of malware threats. On the other hand malware authors try to use obfuscation techniques for evading detection. Unfortunately usual approach (e.g., antivirus software) use signature based method which can easily be evaded. For addressing these shortcomings dynamic methods have been introdu...

Zero-shot learning uses semantic attributes to connect the search space of unseen objects. In recent years, although deep convolutional network brings powerful visual modeling capabilities ZSL task, its features have severe pattern inertia and lack representation relationships, which leads bias ambiguity. response this, we propose Graph-based Visual-Semantic Entanglement Network conduct graph f...

In this work we introduce novel image metrics that can be used with distance-based classifiers or directly to decide whether two input images belong to the same class. While most prior image distances rely purely on comparisons of low-level features extracted from the inputs, our metrics use a large database of labeled photos as auxiliary data to draw semantic relationships between the two imag...

In this paper we propose a model of classification based on the principle of the fuzzy proximity of the terms within the documents. Given the heterogeneous nature of the Arabic documents in our possession, we have studied for this purpose the research model based on the semantic proximity of terms and inspired from the classic Boolean model. Our approach is based on the assumption that more the...

Semantic labeling of coronary arterial segments in invasive angiography (ICA) is important for automated assessment and report generation artery stenosis computer-aided disease (CAD) diagnosis. However, separating identifying individual challenging because morphological similarities different branches on the tree human-to-human variabilities exist. Inspired by training procedure interventional ...

1Universität Stuttgart, 2Columbia University, 3University of Southern California Abstract We investigate formalisms for capturing the relation between semantic graphs and English strings. Semantic graph corpora have spurred recent interest in graph transduction formalisms, but it is not yet clear whether such formalisms are a good fit for natural language data—in particular, for describing how ...

Semantic service composition is an important issue in web service based systems. It is about how to build a new, reusable and value-added service by combining existing semantic web services. In this paper we propose a new hyper-graph based method supporting semantic service composition, which model the service composition problem as a hyper-graph. Then the hyper-graph based service composition ...

In this contribution we propose a variant of a resolution theorem prover which selects resolution steps based on the proportion of models a newly generated clause satisfies compared to all models given in a reference class, which is generated from a subset of the initial clause set. Since the empty clause does not satisfy any models preference is given to such clauses which satisfy few models o...

Various semantic web service discovery techniques have been proposed, many of which perform the profile based service signature (I/O) matching. However, the service I/O concepts are not sufficient to discover web services accurately. This paper presents a new method to enhance the semantic description of semantic web service by using the semantic constraints of service I/O concepts in specific ...