The way participants adapt their search to the specifics of different types of analogies is not fully understood. We compared the effects of two types of semantic distractors. The first were related to C by a semantic relation which had nothing to do with the semantic relation used in the A:B pairs, whereas the second, the so-called ”double distractors”, were not only related to C but also had ...

Structured distributional semantic models aim to improve upon simple vector space models of semantics by hypothesizing that the meaning of a word is captured more effectively through its relational — rather than its raw distributional — signature. In accordance, they extend the vector space paradigm by structuring elements with relational information that decompose distributional signatures ove...

The context type and similarity calculation are two essential features of a distributional similarity scheme (DSS). In this paper, we propose a hierarchical semanticaware DSS that exploits semantic relation words as extra context information to guide the similarity calculation. First, we define and extract five types of semantic relations, and then develop relation-based similarities from the d...

A generic semantic-based framework is presented for the definition and manipulation of class hierarchies for object-oriented languages. The framework is based on the notion of observable of a class, i.e. an abstraction of its semantics when focussing on a behavioral property of interest. By exploiting such a notion, we define the semantic subclass relation, capturing the fact that a subclass pr...

Previous researches on event relation classification primarily rely on lexical and syntactic features. In this paper, we use a Shallow Convolutional Neural Network (SCNN) to extract event-level and cross-event semantic features for event relation classification. On the one hand, the shallow structure alleviates the over-fitting problem caused by the lack of diverse relation samples. On the othe...

Spatial relation terms can generally indicate spatial relations described in natural language context. Their semantic representation is closely related to geographical entities and their characteristics e.g. geometry, scale and geographical feature types. This paper proposes a quantitative approach to explore the semantic relevance of spatial relation terms and geographical feature types of geo...

Recently, two different entropy measures based on the relational structure of English compounds have been used in studies of semantic transparency and lexical decision times. Pham & Baayen (2013) show that the entropy of semantic relations in the modifier family is negatively correlated with semantic transparency. Schmidtke et al. (2015) find that the relational entropy for individual compounds...

This paper presents an unsupervised method for deriving inference axioms by composing semantic relations. The method is independent of any particular relation inventory. It relies on describing semantic relations using primitives and manipulating these primitives according to an algebra. The method was tested using a set of eight semantic relations yielding 78 inference axioms which were evalua...

Recent years have seen the rise of Web data, in particular Linked Data, with, up to now, more than 1000 datasets in the Linked Open Data Cloud (LOD). These datasets are mostly of entity-centric nature and are highly heterogeneous in terms of domains, language, schema, etc. Hence, the vision of uniformly querying such resources in the LOD has a long way to go. While equivalent entity instances a...