Brain-based evidence has implicated the frontal pole of the brain as important for analogical mapping. Separately, cognitive research has identified semantic distance as a key determinant of the creativity of analogical mapping (i.e., more distant analogies are generally more creative). Here, we used functional magnetic resonance imaging to assess brain activity during an analogy generation tas...

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using instance information of the ontology to enrich the original ontology and calculate similarities betwee...

| Nowadays there is an explosion of data repositories available in the Global Information System. In this context, users meet with the problems related to the heterogeneity and distribution of the data repositories. Access to the data may be facilitated by providing semantic views over the repositories that hide all the technical and organizative details associated with them. In this paper it i...

Semantic interoperability is a key issue for the meaningful sharing of geospatial data between multiples geospatial databases. It requires the establishment of semantic mappings between concepts databases’ ontologies. Semantic mappings can be discovered only when semantics is explicit. However, existing concepts’ definitions are not always sufficient to represent the semantic richness of geospa...

In this paper, we address the problem of planning the textual organization of instructions. We take the view that natural language generation (NLG) is a mapping process of diierent levels of conceptual and textual representations. Within this framework , we consider the mapping between the text's semantic representation and its rhetorical structure. We argue that such a mapping is not direct, b...

This paper discusses the enrichment of WordNet data through merging of WordNet concepts and Corpus Pattern Analysis (CPA) semantic types. The 253 CPA semantic types are mapped to the respective WordNet concept. As a result of mapping, the hyponyms of a synset to which a CPA semantic type is mapped inherit not only the respective WordNet semantic primitive but also the CPA semantic type.

Constructing a semantic concept hierarchy covers only part of the problem in building any knowledgebased natural language processing (NLP) system: Language understanding requires mapping from syntactic structures into conceptual (i.e. interlingua) representation (henceforth verb-argument mapping), while language generation requires the inverse mapping. Jacobs [13] proposed a solution in which h...

We present a novel method for visual mapping and localization autonomous vehicles, by extracting, modeling, optimizing semantic road elements. Specifically, our integrates cascaded deep models to detect standardized elements instead of traditional point features, seek improved pose accuracy map representation compactness. To utilize the structural we model lights signs their representative keyp...

Many works in the recent literature introduce semantic mapping methods that use CNNs (Convolutional Neural Networks) to recognize properties images. The types of (eg.: room size, place category, and objects) their classes kitchen bathroom, for category) are usually predefined restricted a specific task. Thus, all visual data acquired processed during construction maps lost only recognized remai...