A bstract. Amongst modellers of natural language comprehension, the suspicion that explicit semantic representations are inherently biased has led many to rely more heavily on the ability of networks to form their own internal semantic representations over the course of training. The concern over explicit semantics, however, betrays a lack of appreciation for the manner in which insidious biase...

In the domain of heterogeneous model composition, semantic adaptation is the “glue” that is necessary to assemble heterogeneous models so that the resulting composed model has well-defined semantics. In this paper, we present an execution model for a semantic adaptation interface between heterogeneous models. We introduce a Domain-Specific Language (DSL) for specifying such an interface explici...

External knowledge bases, both generic and domain specific, available on the Web of Data have the potential of enriching the content of text documents with structured information. We present the Kanopy system that makes explicit use of this potential. Besides the common task of semantic annotation of documents, Kanopy analyses the semantic network that resides in DBpedia around extracted concep...

Many Semantic Web applications provide access to their resources through text-based search queries, using explicit semantics to improve the search results. This paper provides an analysis of the current state of the art in semantic search, based on 35 existing systems. We identify different types of semantic search features that are used during query construction, the core search process, the p...

Different document representation models have been proposed to measure semantic similarity between documents using corpus statistics. Some of these models explicitly estimate semantic similarity based on measures of correlations between terms, while others apply dimension reduction techniques to obtain latent representation of concepts. This paper proposes new hybrid models that combine explici...

This paper introduces Explicit Semantic Ranking (ESR), a new ranking technique that leverages knowledge graph embedding. Analysis of the query log from our academic search engine, SemanticScholar.org, reveals that a major error source is its inability to understand the meaning of research concepts in queries. To addresses this challenge, ESR represents queries and documents in the entity space ...

This paper provides a uniform semantic framework for Topic-Comment Structures in Chinese. It is assumed that the topic element relates to an anaphor occuring in the comment. The comment which contains an unresolved anaphor is semantically underspecified. The semantic interpretation of topic-comment constructions results from the resolution of the anaphoric relation between topic and comment. In...

There is evidence that the explicit lexical-semantic processing deficits which characterize aphasia may be observed in the absence of implicit semantic impairment. The aim of this article was to critically review the international literature on lexical-semantic processing in aphasia, as tested through the semantic priming paradigm. Specifically, this review focused on aphasia and lexical-semant...

Objectives: Semantic Feature Analysis was designed to improve lexical retrieval of aphasic patients via activation of semantic networks of the words. In this approach, the anomic patients are cured with semantic information to assist oral naming. The purpose of this study was to examine the effects of Semantic Feature Analysis treatment on anomia of two nonfluent aphasic patients. Methods: A...

this study aims to investigate the semantic and syntactic features of verbs used in the introduction section of applied linguistics research articles published in iranian and international journals. a corpus of 20 research article introductions (10 from each journal) was used. the corpus was analysed for the syntactic features (tense, aspect and voice) and semantic meaning of verbs. the finding...