Home▸Data Science▸Vector Space Search Engine 2D: TF-IDF Document Retrieval

Vector Space Search Engine 2D: TF-IDF Document Retrieval

Interactive 2D vector space model: type a query and watch it get tokenized, weighted with TF-IDF, and ranked against a document corpus by cosine similarity — with a live scatter-plot projection you can pan and zoom, plus a similarity bar chart.

Data Science2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Type a query and this simulator runs the exact pipeline behind classical text-mining and search-engine retrieval: tokenize the query, weight each term with TF-IDF (or plain term frequency), and rank a fixed corpus of ten documents by cosine similarity in a ~51-dimensional vocabulary space. A 2D scatter plot projects every document and the live query onto a golden-angle circle lattice so you can pan and zoom to watch clusters of topically related documents pull the query point toward them, while a similarity bar chart and the ranked list report the real, full-dimensional math driving the order.

⚙ Under the hood

Type a search query and watch it get tokenized, weighted with TF-IDF, and ranked against a document corpus by cosine similarity — with a live 2D scatter-plot projection you can pan and zoom, plus a similarity bar chart.

text-miningtf-idfinformation-retrievalnlpvector-space-modelcosine-similarity

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install