Span-reachability querying in large temporal graphs
Reachability is a fundamental problem in graph analysis. In applications such as social networks and collaboration networks, edges are always associated with timestamps. Most existing works on reachability queries in temporal graphs assume that two vertices are related if they are connected by a path with non-decreasing timestamps (time-respecting) of edges. This assumption fails to capture the relationship between entities involved in the same group or activity with no time-respecting path connecting them. In this paper, we define a new reachability model, called span-reachability, designed to relax the time order dependency and identify the relationship between entities in a given time period. We adopt the idea of two-hop cover and propose an index-based method to answer span-reachability queries. Several optimizations are also given to improve the efficiency of index construction and query processing. We conduct extensive experiments on eighteen real-world datasets to show the efficiency of our proposed solution.
The rise of community-curated knowledge networks
The Internet put thousands of years of human thought at our fingertips, and enabled billions of people to create content. At least 2.5…
Fill The Sky
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Discord Alternatives, Ranked
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surrealdb/surrealdb
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Building the European Research Area as a social network - MyHub Experiments Wiki
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lieu — alexander cobleigh / cblgh.org
a purpose-built community search engine and how to use it
ProbablyFrens, Contextual Feeds and Intent-Based Discovery
It’s that time of the year—ETHDenver is just around the corner! Index will be there, and if you’re attending, we’d love to connect! But that’s not all—Index has been evolving, bringing new experiences to make discovery more intuitive and personalized.Meet ProbablyFrens: The Matchmaker AgentWe’re introducing Index’s Matchmaker Agent, an autonomous connector that helps you find the friendships, collaborations, and conversations that should already exist. Whether you’re looking for thought partn...
From Social Network to Sense Making
AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora
In the current era of information abundance, transforming vast amounts of unstructured data into structured, machine-readable knowledge remains one of the most significant challenges in artificial intelligence. Knowledge Graphs (KGs) have emerged as the cornerstone technology for this transformation Zhao et al. (2024), providing the semantic backbone for applications ranging from search engines and question answering Wu et al. (2024); Chen et al. (2024c); Zong et al. (2024); Sun et al. (2024b) to recommendation systems Lyu et al. (2024) and complex reasoning tasks Li et al. (2024b). Yet despite their critical importance, current KG construction approaches remain hampered by an inherent paradox: they require predefined schemas created by domain experts, which fundamentally limits their scalability, adaptability, and domain coverage.
Reddit Map
Reddit Map is an open-source tool that lets you navigate Reddit data by displaying clusters of communities with overlapping community members.
A great little thread for distinct social graphs. @sprk.so will definitely be taking ‘hints’ from existing ones (like Bsky), already in the works.
Blaine
Definitely room for UX exploration, but no-ones has a single social graph. It's the biggest lie zuck ever told. 😅 There's a lot of writing on this, but a decent place to start is Erving Goffman; we wear different masks and perform to different audiences depending on social context.
The VLDB Journal - With the rapid development of information technologies, various big graphs are prevalent in many real applications (e.g., social media and knowledge bases). An important...
