The Semantic Link Network model SLN and Resource Space Model RSM are semantic models proposed separately for effectively specifying and managing versatile resources across the Internet. Collaborating the relational semantics of SLN with the classification semantics of the RSM can support richer semantic modeling in applications. This paper introduces the Resource Class Hierarchies into the SLN ...

The sublanguage analysis methodology is based on the theory that texts generated by a group of people possess their own lexical, syntactic, and semantic characteristics. The main thrust of the research reported here is to apply the methodology to Korean document titles, reflecting the fact that there has been little research in applying the methodology for the Korean language although much rese...

Text summarization with the consideration of coherence can be achieved by using discourse processing with the Rhetorical Structure Theory (RST). Additional problems on relational ambiguity may arise, especially in Thai. For example, the use of cue words, i.e. “tae/แต่” (meaning “but”), can be identified as a contrast relation or an elaboration relation. Therefore, we propose the reduction of the...

This paper describes in detail the inferencing rules and operations concerning an ontology formalism previously proposed under Conceptual Structure Theory. The ontology consists of hierarchies of concept, relation and meta-relation types, and formal relationships between them, in particular between arguments of relation and meta-relation types. Inferencing rules are described as well as operati...

In Semantic Role Labeling (SRL) task, the tree structured dependency relation is rich in syntax information, but it is not well handled by existing models. In this paper, we propose Syntax Aware Long Short Time Memory (SA-LSTM). The structure of SA-LSTM changes according to dependency structure of each sentence, so that SA-LSTM can model the whole tree structure of dependency relation in an arc...

This paper describes a system to solve the joint learning of syntactic and semantic dependencies. An directed graphical model is put forward to integrate dependency relation classification and semantic role labeling. We present a bilayer directed graph to express probabilistic relationships between syntactic and semantic relations. Maximum Entropy Markov Models are implemented to estimate condi...

Semantic Link Network SLN is a model of future Semantic Web and Knowledge Web. Based on our previous SLN model, this paper enriches the semantic links and reasoning rules, proposes a computing model for SLN, and develops relevant reasoning and managing mechanisms using a semantic matrix representation of SLN.

Recent advances in automatic knowledge acquisition methods have enabled us to construct massive knowledge bases of semantic relations. Most previous work has focused on semantic relations explicitly expressed in single sentences. Our goal in this work is to obtain valid non-single sentence relation instances, which are not written in any single sentence and may not be even written in a large co...

We present an approach for semantic relation extraction between nominals that combines shallow and deep syntactic processing and semantic information using kernel methods. Two information sources are considered: (i) the whole sentence where the relation appears, and (ii) WordNet synsets and hypernymy relations of the candidate nominals. Each source of information is represented by kernel functi...

This work aims to explore the correlation between the discourse structure of a spoken monologue and its prosody by predicting discourse relations from different prosodic attributes. For this purpose, a corpus of semi-spontaneous monologues in English has been automatically annotated according to the Rhetorical Structure Theory, which models coherence in text via rhetorical relations. From corre...