Web services are the latest attempt to revolutionize large scale distributed computing. They are based on standards which operate at the syntactic level and lack semantic representation capabilities. Semantics provide better qualitative and scalable solutions to the areas of service interoperation, service discovery, service composition, and process orchestration. SAWSDL defines a mechanism to ...

Scene classification is an important issue in computer vision area. However, it is still a challenging problem due to the variability, ambiguity, and scale change that exist commonly in images. In this paper, we propose a novel hypergraph-based modeling that considers the higher-order relationship of semantic attributes in a scene and apply it to scene classification. By searching subnetworks o...

Dataless text classification [Chang et al., 2008] is a classification paradigm which maps documents into a given label space without requiring any annotated training data. This paper explores a crosslingual variant of this paradigm, where documents in multiple languages are classified into an English label space. We use CLESA (cross-lingual explicit semantic analysis) to embed both foreign lang...

Automatic indexing to video data is in strong demand to cope with the increasing amount. We propose an automatic indexing method for television news video, which indexes to shots considering the correspondence of image contents and semantic attributes of keywords. This is realized by rst, (1) classifying shots by graphical feature, and (2) analyzing semantic attributes of accompanying captions....

Complex noun phrases are pervasive in biomedical texts, but are largely underexplored in entity discovery and information extraction. Such expressions often contain a mix of highly specific names (diseases, drugs, etc.) and common words such as “condition”, “degree”, “process”, etc. These words can have different semantic types depending on their context in noun phrases. In this paper, we addre...

In this paper, we introduce a new data representation format for language processing, the syntactic and semantic graphs (SSGs), and show its use for call classification in spoken dialog systems. For each sentence or utterance, these graphs include lexical information (words), syntactic information (such as the part of speech tags of the words and the syntactic parse of the utterance), and seman...

The database of Genotypes and Phenotypes (dbGaP) is archiving the results of different Genome Wide Association Studies (GWAS). dbGaP has a multitude of phenotype variables, but they are not harmonized across studies. We proposed a method to standardize phenotype variables by classifying similar variables based on semantic distances. We first extracted variables description, enriched them using ...

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR ou...

In this paper we discuss several issues related to automated text classification of web sites. We analyze the nature of web content and metadata and requirements for text features. We present an approach for targeted spidering including metadata extraction and opportunistic crawling of specific semantic hyperlinks. We describe a system for automatically classifying web sites into industry categ...

Proper nouns form an open class, making the incompleteness of manually or automatically learned classification rules an obvious problem. The purpose of this paper is twofold:first, to suggest the use of a complementary "backup" method to increase the robustness of any hand-crafted or machinelearning-based NE tagger; and second, to explore the effectiveness of using more fine-grained evidence--n...