Search results for " Embedding"
showing 4 items of 84 documents
Predictive First-principles Modeling of a Photosynthetic Antenna Protein : The Fenna-Matthews-Olson Complex
2020
High efficiency of light harvesting in photosynthetic pigment-protein complexes is governed by evolutionary-perfected protein-assisted tuning of individual pigment properties and inter-pigment interactions. Due to the large number of spectrally overlapping pigments in a typical photosynthetic complex, experimental methods often fail to unambiguously identify individual chromophore properties. Here we report a first principles-based modeling protocol capable of predicting properties of pigments in protein environment to a high precision. The technique was applied to successfully uncover electronic properties of the Fenna-Matthews-Olson (FMO) pigment-protein complex. Each of the three subunit…
Multi-word Lexical Units Recognition in WordNet
2022
WordNet is a state-of-the-art lexical resource used in many tasks in Natural Language Processing, also in multi-word expression (MWE) recognition. However, not all MWEs recorded in WordNet could be indisputably called lexicalised. Some of them are semantically compositional and show no signs of idiosyncrasy. This state of affairs affects all evaluation measures that use the list of all WordNet MWEs as a gold standard. We propose a method of distinguishing between lexicalised and non-lexicalised word combinations in WordNet, taking into account lexicality features, such as semantic compositionality, MWE length and translational criterion. Both a rule-based approach and a ridge logistic regre…
Biased graph walks for RDF graph embeddings
2017
Knowledge Graphs have been recognized as a valuable source for background information in many data mining, information retrieval, natural language processing, and knowledge extraction tasks. However, obtaining a suitable feature vector representation from RDF graphs is a challenging task. In this paper, we extend the RDF2Vec approach, which leverages language modeling techniques for unsupervised feature extraction from sequences of entities. We generate sequences by exploiting local information from graph substructures, harvested by graph walks, and learn latent numerical representations of entities in RDF graphs. We extend the way we compute feature vector representations by comparing twel…
Some characterisations of groups in which normality is a transitive relation by means of subgroup embedding properties
2018
[EN] In this survey we highlight the relations between some subgroup embedding properties that characterise groups in which normality is a transitive relation in certain universes of groups with some finiteness properties.