Certain previous researches attempted to characterize how association memory works. The word meanings derived from LSA (latent semantic analysis) are usually showed highly related to the performance of forward association memory. A naı̈ve postulation would assume that the mechanisms for that relationship are mainly due to the processes of semantic similarity. The present work not only validates ...

For multi-level semantic structure, the asymmetry of similarity between semantic concepts, as well as the different correlation of semantics between the children nodes and father node, this dissertation proposed a novel similarity calculation method of image semantic based on the probabilistic weighting. This method combines the image feature mapping the visual characteristics of the underlying...

Calculating the semantic similarity between sentences is a long dealt problem in the area of natural language processing. The semantic analysis field has a crucial role to play in the research related to the text analytics. The semantic similarity differs as the domain of operation differs. In this paper, we present a methodology which deals with this issue by incorporating semantic similarity ...

Lexical co-occurrence counts from large corpora have been used to construct highdimensional vector-space models of language.. Distances between word vectors extracted from these models are generally considered to reflect semantic similarity. Implicit in this assumption is that ‘semantic distance’ measurements correspond to human intuitions. This paper investigates the validity of one such measu...

Semantic similarity is the essential part of automatic question answering system, and the computation of semantic similarity based on ontology can provide more various semantic information compared with the traditional method. In this paper, we firstly propose a semantic similarity algorithm used in the sentence similarity computation, combining relations of semantics, hierarchical structure an...

The way we model semantic similarity is closely tied to our understanding of linguistic representations. We present several models of semantic similarity, based on di ering representational assumptions, and investigate their properties via comparison with human ratings of verb similarity. The results o er insight into the bases for human similarity judgments and provide a testbed for further in...

Automatic service discovery in heterogeneous environment is becoming one of the challenging problems for applications in semantic web, wireless sensor networks, etc. It is mainly due to the lack of accurate semantic similarity assessment between profile attributes of user request and web services. Generally, lexical semantic resources consist of corpus and domain knowledge. To improve similarit...

Semantic similarity aims at establishing resemblance by interpreting the meaning of the objects being compared. The Semantic Web can benefit from semantic similarity in several ways: ontology alignment and merging, automatic ontology construction, semantic-search, to cite a few. Current approaches mostly focus on computing similarity between nouns. The aim of this paper is to define a framework...

Semantic similarity is a fundamental notion in GIScience for achieving semantic interoperability among geospatial data. Until now, several semantic similarity models have been proposed; however, few of these models address the issues related to the assessment of semantic similarity in ad hoc network. Also, several models are based on a definition of concepts where features are independent, an a...