Publications related to Graph database

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Lawful Interception (LI) is a legal obligation of Communication Service Providers (CSPs) to provide interception capabilities to Law Enforcement Agencies (LEAs) in order to gain insightful data from network communications for criminal proceedings, e.g., ne ...

New York2023

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

Jibril Albachir Frej, Tatjana Nazaretsky

The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networks with Knowledge Graphs (KGs) to achieve richer representations of learners ...

2023

GRAMM: Fast CGRA Application Mapping Based on A Heuristic for Finding Graph Minors

Mirjana Stojilovic, Guanglei Zhou

A graph H is a minor of a second graph G if G can be transformed into H by two operations: 1) deleting nodes and/or edges, or 2) contracting edges. Coarse-grained reconfigurable array (CGRA) application mapping is closely related to the graph minor problem ...

2023

Using Cloud Functions as Accelerator for Elastic Data Analytics

Anastasia Ailamaki, Haoqiong Bian, Tiannan Sha

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines runn ...

ACM2023

Acquaintances or Familiar Strangers? How Similarity and Spatial Proximity Shape Neighbour Relations within Residential Buildings

Maxime Carl Felder, Guillaume Favre

While scholars have long established that city dwellers choose with whom to develop relationships on the basis of social proximity, spatial proximity remains the basis for neighbour relations involving greetings, social conversation, and the exchange of se ...

ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD2023

Deep MinCut: Learning Node Embeddings by Detecting Communities

Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Chi Thang Duong, Trung-Dung Hoang

We present Deep MinCut (DMC), an unsupervised approach to learn node embeddings for graph -structured data. It derives node representations based on their membership in communities. As such, the embeddings directly provide insights into the graph structure ...

ELSEVIER SCI LTD2022

Distributed Graph Learning With Smooth Data Priors

Pascal Frossard, Mireille El Gheche, Isabela Cunha Maia Nobre

Graph learning is often a necessary step in processing or representing structured data, when the underlying graph is not given explicitly. Graph learning is generally performed centrally with a full knowledge of the graph signals, namely the data that live ...

IEEE2022

Quantization for Distributed Processing and Learning of Structured Data

Isabela Cunha Maia Nobre

In the domains of machine learning, data science and signal processing, graph or network data, is becoming increasingly popular. It represents a large portion of the data in computer, transportation systems, energy networks, social, biological, and other s ...

EPFL2022

The power of adaptivity in source identification with time queries on the path

Patrick Thiran, Gergely Odor, Victor Cyril L Lecomte

We study the problem of identifying the source of a stochastic diffusion process spreading on a graph based on the arrival times of the diffusion at a few queried nodes. In a graph

G=(V,E)

, an unknown source node

v^* \in V

is drawn uniformly at random, ...

2022

Graph Representation Learning with Optimal Transport: Analysis and Applications

Effrosyni Simou

In several machine learning settings, the data of interest are well described by graphs. Examples include data pertaining to transportation networks or social networks. Further, biological data, such as proteins or molecules, lend themselves well to graph- ...

EPFL2022

Graph database

Graph Chatbot

Chat with Graph Search

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

GRAMM: Fast CGRA Application Mapping Based on A Heuristic for Finding Graph Minors

Using Cloud Functions as Accelerator for Elastic Data Analytics

Acquaintances or Familiar Strangers? How Similarity and Spatial Proximity Shape Neighbour Relations within Residential Buildings

Deep MinCut: Learning Node Embeddings by Detecting Communities

Distributed Graph Learning With Smooth Data Priors

Quantization for Distributed Processing and Learning of Structured Data

The power of adaptivity in source identification with time queries on the path

Graph Representation Learning with Optimal Transport: Analysis and Applications

Using Cloud Functions as Accelerator for Elastic Data Analytics

Distributed Graph Learning With Smooth Data Priors

GRAMM: Fast CGRA Application Mapping Based on A Heuristic for Finding Graph Minors

Quantization for Distributed Processing and Learning of Structured Data

Acquaintances or Familiar Strangers? How Similarity and Spatial Proximity Shape Neighbour Relations within Residential Buildings

Deep MinCut: Learning Node Embeddings by Detecting Communities

P3LI5: Practical and confidEntial Lawful Interception on the 5G core

Finding Paths for Explainable MOOC Recommendation: A Learner Perspective

The power of adaptivity in source identification with time queries on the path

Graph Representation Learning with Optimal Transport: Analysis and Applications