(2012): A node semantic similarity schema-matching method for multi-version Web This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make...

Schema/ontology matching is a critical problem in many application domains, such as, semantic web, schema/ontology integration, data warehouses, e-commerce, catalog matching, etc. Many diverse solutions to the matching problem have been proposed so far. In this paper we present a taxonomy of schema-based matching techniques that builds on the previous work on classifying schema matching approac...

Semantic web is dependent on extensive knowledge management by inter linking resources on the web using matching techniques. This role is played by the progressing domain of ontology matching, by introducing ontology matching tools. The focus of these matching tools is limited to matching techniques and automation only, rather than expressive formal representation of alignments. We propose Medi...

The N400 ERP is an electrophysiological index of semantic processing. Its amplitude varies with the semantic category of words, their concreteness, or whether their meaning matches that of a preceding context. The results of a number of studies suggest that these effects could be markedly reduced or suppressed for stimuli that are repeated. Nevertheless, we have recently shown that significant ...

Language-induced asymmetry to single word reading has been well investigated in past research. Less known are the complex processes and related asymmetries occurring when a is compared with previous one, according specific tasks. To this end, we used paradigm based on 80 sequential pair comparisons three blocked tasks: phonological, semantic orthographical matching judgment. Participants had de...

Observing a set of images and their corresponding paragraph-captions, challenging task is to learn how produce semantically coherent paragraph describe the visual content an image. Inspired by recent successes in integrating semantic topics into this task, paper develops plug-and-play hierarchical-topic-guided image generation framework, which couples extractor with deep topic model guide learn...