Skip to main content
Share Your Experience: Take the 2024 Developer Survey

Questions tagged [graphs]

For the nodes and links sense of graph; use the visualization tag for the charting sense.

Filter by
Sorted by
Tagged with
0 votes
0 answers
13 views

graph signal in GNN

I am reading several materials about graph signal processing for a thesis on Graph Neural Network and i see that a graph signal is defined as a vector so each node signal is a scalar. In practice, a ...
endeavor's user avatar
  • 101
1 vote
1 answer
31 views

In a Computational Graph, how to calculate the total upstream gradient of a node with multiple upstreams?

Given a Computation Graph with a node (like the one below), I understand that I can use the upstream gradient dL/dz to calculate all of my downstream gradients. But what if there are multiple ...
Ibrahim's user avatar
  • 111
0 votes
0 answers
4 views

Trying to turn on owid-grapher's local server, I get "Waiting for MySQL to come up" forever and localhost:8080 doesn't return anything

I wanted to experiment with Our World in Data's Grapher. I followed the local development setup instructions. Most of the code worked. The Docker container is up. I can access the MySQL database with ...
J Eti's user avatar
  • 101
1 vote
0 answers
24 views

Graph Clustering algorithms when both nodes *and* edges have features (numerical, categorical and potentially even temporal!)

I'm trying to figure out how much complexity I can get away with and am looking for model recommendations. I have transactional data on hand - the features being customer id, customer balance, ...
MergeMonster's user avatar
0 votes
0 answers
9 views

Predicting a finite multi-set from a finite set given vector-valued data

I am unsure in how to approach this problem, which is a supervised learning task, and was looking for ideas on how to tackle it since I am kinda confused. Abstract description: I have a source set $S:=...
The Bosco's user avatar
  • 101
0 votes
0 answers
171 views

Convert specific domain knowledge text to a knowledge graph

As part of this semester assignment , I'm working on a project that aims to to represent the knowledge in "PMBOK 6th edition, section 11: Project Risk Management (page 395 -> 458)" and the knowledge ...
Wissem Boujlida's user avatar
0 votes
0 answers
17 views

how to derive this negative sampling approximation for graphs?

I am watching CS224W video (https://www.youtube.com/watch?v=Xv0wRy66Big&list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn&index=8) and have some issue understanding the following approximation: Does ...
username123's user avatar
0 votes
0 answers
65 views

Train test split in Graph Convolution Network for image classification

I am trying to construct a GCN for image classification where each pixel is a single node in the graph. However I want to train and test the model within the same graph, so I constructed a single ...
foobar's user avatar
  • 1
0 votes
0 answers
28 views

How to Use Graph Learning Libraries to Predict Edges on a Graph where Each Node Has an Embedding?

An undirectional graph $\mathcal{G}$ has the set of nodes $\mathcal{N}$ where each node has an associated unique embedding of $512$ dimensions. Note that the embeddings themselves are fixed, and not ...
Della's user avatar
  • 335
1 vote
1 answer
85 views

When visualizing graph nodes, should I use apply PCA to node2vec embedding?

I am trying to visualize graph nodes using node2vec embedding. The node2vec embeddings has lengths of 50~100 dimensions. I have two plans: use umap to project node2vec embeddings to 2D space use PCA ...
Sijie Chen's user avatar
1 vote
1 answer
127 views

Trouble Training GNN for Binary Node Classification Task

I am using a GNN to solve a problem in which I have a query target and an undirected graph. My goal is to emit a subset of nodes in the graph (via a node-wise binary prediction) whose features sum to ...
mt_'s user avatar
  • 11
0 votes
0 answers
61 views

What is degree assortativity coefficient of a complete undirected graph?

Because it computes the correlation coefficient of degrees and the correlation coefficient of constant arrays is not defined, networkx library returns ...
Neo's user avatar
  • 3
1 vote
2 answers
124 views

How to compute edge and node bottleneck coefficients in a weighted directed graph using networkx?

I am trying to analyze a weighted network, and I am focusing on identifying the bottleneck nodes and edges coefficients. I have never done that before on Python and I have the following code: ...
Bree's user avatar
  • 9
1 vote
0 answers
441 views

NetworkX: Subgraph matching

Trying to match a Query subgraph to a Target graph, where: Query: and Target: As I understand matching in this case should return tuples of matching nodes: ...
dokondr's user avatar
  • 295
0 votes
1 answer
126 views

Matching nodes in two directed graphs

How to match a node of graph X with the same node in graph G if: Every node has only one feature: text string, and Nodes in different graphs are considered to be equal if: ...
dokondr's user avatar
  • 295
1 vote
2 answers
78 views

How to cluster components of a graph containing text data?

Suppose that I have a graph that has components like the image below. Graph nodes contain text data (titles) and the edges data is the similarity (percentage). I know that each component represents a ...
Reza Shabrang's user avatar
1 vote
1 answer
81 views

What are good Bipartite Graphs Algorithms?

Currently, I have a dataset with pairs . The idea is to detect any anomaly in these relationships. I was able to just use pandas to do the analysis so far. |Customer|Agent|Duration|Marks|etc |C1.......
mehmat's user avatar
  • 33
0 votes
0 answers
198 views

Python - stock price for different stocks plotting (without yfinance)

I have a dataset which contains a few stocks in a range of dates. I searched in internet but most of the solutions gives solutions with yfinance and I'm not ...
Michael W's user avatar
1 vote
0 answers
23 views

What is purpose of diffusion matrix? What is its role in graph clustering? How do it serve its purpose by equation?

As titled, I am not quite sure what is purpose of Diffusion Matrix, which is support to clustering graph. From this article (https://arxiv.org/pdf/2006.05582v1.pdf) I am might able to compute the ...
Phạm Tâm's user avatar
1 vote
0 answers
19 views

What kind of object detection model is required?

I have some images, and my task is to build an object detection model for detecting tables and equipment photos in the image. The target would be detecting objects (table and equipment), so I can crop ...
sksoumik's user avatar
  • 111
0 votes
1 answer
153 views

METIS requests ~1000 TB of memory for problem

I am attempting to use METIS (configured for 64-bit, with a Python interface) to perform some weighted graph partitioning, but am immediately being hit with a memory allocation failure: ...
Mandias's user avatar
2 votes
1 answer
45 views

Method or tool to simulate weighted graphs with a specified weighted degree sequence

Are you aware of a method or tool to simulate a graph with that has a specified weighted degree sequence? They would be used to generate a distribution of bootstrap replicates.
Ruairi O'Sullivan's user avatar
1 vote
1 answer
123 views

How to describe this UMAP connectivity figure

I generated this UMAP connectivity diagram of my research data. How do I interpret/describe this plot regarding the UMAP connectivity? Is it correct to say that: As there is a lot of connectivity ...
Joe's user avatar
  • 147
0 votes
1 answer
33 views

May high closeness centrality in email graph be interpreted as high involvement?

I have a network graph where nodes are email addresses and their connections are emails they send to each other. I have calculated closeness centrality for each node and got couple with very high ...
Ir8_mind's user avatar
  • 183
1 vote
1 answer
855 views

Building a graph out of a large text corpus

I'm given a large amount of documents upon which I should perform various kinds of analysis. Since the documents are to be used as a foundation of a final product, I thought about building a graph out ...
kevin_was_here's user avatar
2 votes
0 answers
51 views

Task of regression on graphs

Which tools are available to extract features from a graph. After that, I would like to perform regressions on those features. Initially, I was thinking about using the adjacency matrix of the graph. ...
Tereso del Río Almajano's user avatar
0 votes
1 answer
86 views

How can I store sources, effective dates, and confidence for every property in a knowledge graph?

What I am wanting to do is ensure that every property in a knowledge base comes from at least one source. I would like to ensure that every edge is spawned (or at least explained) by some event, like ...
AJAr's user avatar
  • 103
3 votes
4 answers
2k views

How to perform inductive train/test split for GraphSAGE classification

Let's say I have a network that consists of a single weakly connected component. From various papers I've seen that if you want to use inductive GNNs like GraphSAGE, it is advisable to split your ...
Tomaž Bratanič's user avatar
2 votes
0 answers
31 views

Probability distributions for Directed Cyclic Graphs

Given a directed cyclic graph where vertex A is 'infected', and there are different infection probabilities between each node, what is the best approach towards computing the conditional probability $...
Jonas Hjulstad's user avatar
0 votes
1 answer
81 views

Algorithms for Vertex or Node Correspondence

Given a graph G, and another graph with the same number of vertices G’, one can define a vertex correspondence function f, from the vertex set of G to the vertex set of G’. The correspondence function ...
Matthew Crawford's user avatar
0 votes
0 answers
38 views

How to unify weights in my dataset

I have a symptom-disease network that consists of four attributes: symptom, disease, co-occurrence and TF-IDF. I'm considering the TF-IDF attribute as the weight of my network edges and symptom and ...
Alireza Azhdari's user avatar
1 vote
0 answers
41 views

Tableau - Filter Buttons not filtering correctly

I created filter buttons to use as a filter for 6 category's (measures) in Tableau Public (latest version) so when you click on them the values for each display on my "Military Enrollment By ...
Nat's user avatar
  • 11
1 vote
0 answers
19 views

Predicting the amount of new nodes discovered if a known node is extended in a graph

I'm currently working on a problem relating to Discord servers (sort of like a group chat within a social media platform), where I have a program recursively joining servers, looking for invites, and ...
Alec Petridis's user avatar
2 votes
0 answers
330 views

Graph legend for plot in Base R for class differentiated data gives incorrect representation of actual category

I am new to R. While working on my university assignments, I found that legends for Base R plot do not show correct information, hence I switched to ggplot2 wherever legends were needed. I observed ...
Vanjuli's user avatar
  • 21
2 votes
1 answer
42 views

Return the gradient and y intercept (m, b) to create two lines to best fit the data

I have been working on this task for a few hours now and have been unsuccessful with getting the target result. I have tried using multiple methods of trying to split the dataset using different ...
Sultan's user avatar
  • 21
1 vote
0 answers
50 views

Graph Pattern Matching Library

Assume that in an application, the user gives us a graph and we want to consider it as a pattern and find all occurrences of the pattern in a graph database (like neo4j). If we knew what the pattern ...
Shayan's user avatar
  • 111
0 votes
0 answers
104 views

Using MySQL Common Table Expressions to solve the travelling salesman problem

The problem I'm trying to solve is very similar to the travelling salesman problem, where there are many paths between nodes in the database. I've tried to edit my example to fit into this well-known ...
Greg's user avatar
  • 101
1 vote
0 answers
40 views

weakly connected (or disconnected) graph enhancement

I'm trying to model a collection of security alerts into graph representation. Each alert consists of 0 or more objects that represent IP addresses, users, hostnames and so on. I consider two objects ...
Yair stern's user avatar
1 vote
0 answers
19 views

Node embeddings and densely connected graphs

I have a dataset of users and their interests (represented by categories) and I’m trying to embed the graph which results from connecting users if they have a common interest, so I’ll add an edge for ...
Adam's user avatar
  • 11
1 vote
1 answer
107 views

Is there a metric for "cliquiness" for social graphs?

Regarding social network graphs, let us say that I am connected to 10 people, and that each of them are connected to 10 people. At one extreme this means that I have 100 unique $2^{nd}$ degree ...
JnBrymn's user avatar
  • 111
0 votes
0 answers
12 views

Which kind of technique is used for classifying a graph datastructure?

I have a 3D surface from which I extract certain spatial parameters like extremas and their locations (a.k.a coordinates), which then I convert into a bipartite graph with distance between them as ...
Tarun Maganti's user avatar
1 vote
2 answers
29 views

Low-dimensional path representation learning

I have a graph (ex: map) and multiple sequences of ids representing different paths. A vertex represents a region/area An edge between 2 vertices : a crossing from a region to another A graph path (...
floriandaniel's user avatar
1 vote
2 answers
904 views

How to model a 3D graph into a vector so that I can feed it into a classification algorithm?

I have a 3D graph like below: Ref: google images It has 2 angles as X and Y and the Z axis is amplitude value (Each 3D graph is representing a pixel). I want to model this into some useful data ...
Tarun Maganti's user avatar
1 vote
0 answers
57 views

How to create a graph network (Networkx) from the solution of Ordinary differential equations?

I have a list of Nodes. Suppose, N =["1","2","3","4"] # there can be different number of nodes And I have solved the ...
Atom Store's user avatar
2 votes
1 answer
582 views

Negative sampling for graph representation learning

I was watching a lecture about graph representation learning (from here) and got a little bit confusing about how they define the negative samping procedure. In the presentation J. Leskovec briefly ...
elfinorr's user avatar
0 votes
1 answer
889 views

What does my learning curve indicate?

I have performed logistic regression. And I am getting an accuracy of 77% with my current model. I divided my training set into cross validation set and train set. And I plotted a learning curve (...
Mauj Mishra's user avatar
2 votes
0 answers
110 views

Is there a node embedding method that is portable between graphs?

I have several graphs whose nodes I want to encode to later process them with a neural network. I want the embeddings to take into account the topology of the graph around the nodes I am embedding, ...
Charles G's user avatar
1 vote
1 answer
77 views

Stacked Bar Chart in R

I wondered if someone could help with a re-labelling 'fill' variables ' and the x-axis on a stacked bar chart please? My ambition is to: Express the fill variable(s) as of six domains in the health ...
EB3112's user avatar
  • 203
1 vote
1 answer
28 views

Seeding a graph to simulate effect of a vaccine on disease spread

I am modeling an Independent cascade model in graph diffusion, by simulating a disease. I have an undirected graph, and I need to choose 50 nodes to vaccinate before the disease starts spreading, and ...
Daniel's user avatar
  • 131
0 votes
0 answers
1k views

seaborn heatmap - x axis - repeated values

I'm in trouble creating a heatmap using a CSV file. csv data is in a format like below here is a code ...
Hello-experts's user avatar

1
2 3 4 5