graph

问题 Very similar to the question posted here I have the following nodes: Article and Words. Each word is connected to an article by a MENTIONED relationship. I need to query all articles that have common words where the list of common words is dynamic. From the clients perspective, I am passing back a list of words and expecting back a results of articles that have those words in common. The following query does the job WITH ["orange", "apple"] as words MATCH (w:Word)<-[:MENTIONED]-(a:Article)-[

问题 I am trying to solve the reconstruct itinerary problem (https://leetcode.com/problems/reconstruct-itinerary/) in Scala using functional approach. Java solution works but Scala doesn't. One reason I found out was the hashmap is being updated and every iteration has the latest hashmap (even when popping from recursion) which is weird. Here is the solution in Java: import java.util.ArrayList; import java.util.HashMap; import java.util.LinkedList; import java.util.List; import java.util.Map;

问题 In the AWS Neptune documentation it says it is Apache TinkerPop Gremlin compatible but it only refers to online transaction processing (OLTP) type of graph traversal queries. I haven't seen anything about long-running online analytical processing (OLAP) GraphComputer queries. Is it possible to execute OLAP queries on graphs stored in AWS Neptune graph database service? 回答1: I was at ReInvent and had a chance to talk to Brad about it. For the immediate future it’s all OLTP. only one query per

问题 In the AWS Neptune documentation it says it is Apache TinkerPop Gremlin compatible but it only refers to online transaction processing (OLTP) type of graph traversal queries. I haven't seen anything about long-running online analytical processing (OLAP) GraphComputer queries. Is it possible to execute OLAP queries on graphs stored in AWS Neptune graph database service? 回答1: I was at ReInvent and had a chance to talk to Brad about it. For the immediate future it’s all OLTP. only one query per

问题 In the AWS Neptune documentation it says it is Apache TinkerPop Gremlin compatible but it only refers to online transaction processing (OLTP) type of graph traversal queries. I haven't seen anything about long-running online analytical processing (OLAP) GraphComputer queries. Is it possible to execute OLAP queries on graphs stored in AWS Neptune graph database service? 回答1: I was at ReInvent and had a chance to talk to Brad about it. For the immediate future it’s all OLTP. only one query per

问题 I'm studying Tarjan's algorithm for strongly-connected components and the way it works is clear to me. Anyway there's a line I don't understand: // Consider successors of v for each (v, w) in E do if (w.index is undefined) then // Successor w has not yet been visited; recurse on it strongconnect(w) v.lowlink := min(v.lowlink, w.lowlink) else if (w.onStack) then // Successor w is in stack S and hence in the current SCC v.lowlink := min(v.lowlink, w.index) // ************* end if end for I

问题 I'm studying Tarjan's algorithm for strongly-connected components and the way it works is clear to me. Anyway there's a line I don't understand: // Consider successors of v for each (v, w) in E do if (w.index is undefined) then // Successor w has not yet been visited; recurse on it strongconnect(w) v.lowlink := min(v.lowlink, w.lowlink) else if (w.onStack) then // Successor w is in stack S and hence in the current SCC v.lowlink := min(v.lowlink, w.index) // ************* end if end for I

问题 I understand there are 3 common ways to represent graphs: Adjacency Matrix Adjacency List Edge list That said, problems I’ve solved on LeetCode often use matrices and the solution requires DFS or BFS. For example, given the matrix below, find if a target string exists when you go left, right, up, and down (but not diagonal). [ [‘a’,‘p’,’p’], [‘e’,’a’,’l’], [‘r’,’t’,’e’] ] This required a DFS approach. Is this because this matrix represents a graph or does DFS and BFS apply to matrices too and

问题 I have a DataFrame in pandas with information about people location in time. It is about 300+ million rows. Here is the sample where each Name is assigned to a unique index by group.by and sorted by "Name" and "Year": import pandas as pd inp = [{'Name': 'John', 'Year':2018, 'Address':'Beverly hills'}, {'Name': 'John','Year':2018, 'Address':'Beverly hills'}, {'Name': 'John', 'Year':2019, 'Address':'Beverly hills'}, {'Name': 'John', 'Year':2019, 'Address':'Orange county'}, {'Name': 'John',

问题 I am making a modified SIR model with an added vaccination parameter V. InitIALLY all the nodes in the graph are susceptible and there are a few initially infected people. The initial infected people neighbours are first vaccinated with prob w (which means they cant be infected) and then they are infected with prob b. The total number of vaccinated people is controlled by Vl which is a fraction of the total population. Here is my code- import networkx as nx import random import scipy from