personalized-pagerank

Python Implementation for Random Walk with Restart (RWR)

(Personalized) Page-Rank computation using PyTorch

Dependency-free Python CLI for social graph search, PageRank, recommendations, autocomplete, and BFS exploration.

[ICLR 2024] "Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs"

[ICLR 2024] "Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs"

Unsupervised categorization of customer reviews into aspect categories using Personalized Page Rank

Python social graph analysis and recommendation system using PageRank, Personalized PageRank, BFS, trie autocomplete, inverted index search, and Levenshtein suggestions.

A Javascript package for computing personalized pagerank.

Demonstration of vectorization of movies, recommendation using collaborative filtering and classification.

Centrality-aware GraphRAG retrieval planner — drop-in layer over any vector DB. Zero LLM in the query path; MCP server included.

Recsys network algorithm designed to return a configurable node neighborhood for nodes of a given type on a bipartite graph.

Implementation of the pagerank algorithm in go

One random walk, three teleport vectors — a live, interactive guide to PageRank vs Personalized PageRank. No build, no dependencies, all computed in your browser.

Explainable recipe recommendations using a culinary knowledge graph and Personalized PageRank

High-performance Rust engine for optimizing LLM context windows by analyzing deep semantic dependencies in code, improving token efficiency and reducing possible hallucinations.

Synapse — a counterfactual edge-ablation protocol testing whether a retrieval system's explanation actually caused its ranking.

A reproducible benchmark for incomplete-cue personal mobility recall, comparing BM25, multilingual E5 dense retrieval, and dense-seeded graph retrieval with RRF/PPR diagnostics.

Personalized version of PageRank. BM25 algorithm to find top ranked publications for a query.

Operational Runtime Behavior Mining for Open-Source Supply Chain Security

A second brain that argues back — a typed-graph (graph-RAG) retrieval engine over an Obsidian vault: edge-weighted Personalised PageRank, multi-lens Council Mode, and retrieval quality measured at MRR 0.69→0.88.