Existing whole-body human pose estimation methods mostly segment the parts of body’s hands and feet for specific processing, which not only splits overall semantics body, but also increases amount calculation complexity model. To address these drawbacks, we designed a novel semantic–structural graph convolutional network (SSGCN) tasks, leverages structure to analyze keypoints through improves a...

In this article, we examine an algorithm for document clustering using a similarity graph. The graph stores words and common phrases from the English language as nodes and it can be used to compute the degree of semantic similarity between any two phrases. One application of the similarity graph is semantic document clustering, that is, grouping documents based on the meaning of the words in th...

There are two key issues for information diffusion in blogosphere: (1) blog posts are usually short, noisy and contain multiple themes, (2) information diffusion through blogosphere is primarily driven by the “word-of-mouth” effect, thus making topics evolve very fast. This paper presents a novel topic tracking approach to deal with these issues by modeling a topic as a semantic graph, in which...

Person disambiguation monitors web appearances of a person by disambiguating information belonging to different people sharing the same name. In this paper we extend person disambiguation to incorporate the abstract notion of identity. This extension utilises semantic web technologies to represent the identity of the person to be found and the web resources to be disambiguated as semantic graph...

Machine Translation, i.e., translating one kind of natural language to another kind of natural language by using a computer system, is a very important research branch in Artificial Intelligence. Yao developed a method of translation that he called “Lexical-Semantic Driven”. In his system he introduced 49 “relation types” including case relations, event relations, semantic relations, and comple...

Many tasks in NLP stand to benefit from robust measures of semantic similarity for units above the level of individual words. Rich semantic resources such as WordNet provide local semantic information at the lexical level. However, effectively combining this information to compute scores for phrases or sentences is an open problem. Our algorithm aggregates local relatedness information via a ra...

RDF data can be thought of as a graph where the subject and objects are vertices and the predicates joining them are edge attributes. Despite decades of research in graph theory, very little of this work has been applied to RDF data sets and it has been largely ignored by the Semantic Web research community. We present a case study of triangle finding, where existing algorithms from graph theor...