Titlebook: Complex Networks & Their Applications IX; Volume 2, Proceeding Rosa M. Benito,Chantal Cherifi,Marta Sales-Pardo Conference proceedings 2021

Virtues

Incorporating Domain Knowledge into Health Recommender Systems Using Hyperbolic Embeddingsas it helps to provide meaningful and personalised recommendations catering to the individual’s health needs. With recent advances in representation learning enabling the hierarchical embedding of health knowledge into the hyperbolic Poincaré space, this work proposes a content-based recommender sys

解凍

Image Classification Using Graph-Based Representations and Graph Neural Networksthe-art deep learning method for image classification since these models are naturally suited to problems where the coordinates of the underlying data representation have a grid structure. On the other hand, in recent years, there is a growing interest in mapping data from different domains to graph

Anecdote

Graph-Based Topic Extraction from Vector Embeddings of Text Documents: Application to a Corpus of Nelop efficient methods that can provide insights into emerging content areas, and stratify unstructured corpora of text into ‘topics’ that stem intrinsically from content similarity. Here we present an unsupervised framework that brings together powerful vector embeddings from natural language proces

Expertise

Antimicrobial

偏狂癥

Connecting the Dots: Integrating Point Location Data into Spatial Network Analysesen not natively tied to our networks. Instead, they can occur as point data (such as store, train station, and domicile locations) and/or grid data (such as socio-economic and aggregate area data). Here we present a set of methods to integrate point data into an augmented transportation network. Thi

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