Projet_test

Projet_test2

This example visualizes a force-directed graph of musical artist recommendations, where nodes represent artists and links show association rules derived from a market-basket analysis of listening data. The graph encodes the support value of each co-occurrence, and hovering highlights connected nodes. The visualization is built with D3 v4, using `d3.forceSimulation` for layout and `d3.forceLink` plus `d3.forceManyBody` for physical simulation. Artist images and their top five tags are loaded from a separate CSV and displayed, while an input field lets users search and filter the graph.

92% match

Projet 4

This visualization displays a force-directed network of music artists based on association rules from listener data, showing which artists are frequently recommended together. Nodes represent artists, with node size and link thickness reflecting the support values from the dataset. The visualization uses d3.forceSimulation to position nodes and SVG for rendering, with tags and artist names as labels. It includes a search feature that filters and highlights connected artists, sourced from CSV files containing artist tags and recommendation rules.

91% match

Projet_test3

This interactive network visualization maps artist recommendations from a CSV of association rules, showing connections between musicians with link thickness scaled by support values. The D3.js v4 code employs `d3.forceSimulation` with force-directed layout, applying `d3.forceLink` and `d3.forceManyBody` physics, while styling nodes as SVG circles that display artist photos via URL when available. Hovering triggers a tooltip, and each node can be clicked to display its top five tags from the supplementary CSV data. The visualization uses a categorical color scheme (`d3.schemeCategory20`) and scales node radius by artist count.

Projet(test) : Artists recommendation

This visualization shows music artist recommendations as a force-directed network graph, where each node represents an artist and links indicate association rules derived from the dataset. The graph uses D3 v4’s `d3.forceSimulation` with `d3.forceLink`, `d3.forceManyBody`, and `d3.forceCenter` to position nodes, while link stroke-width encodes support values from the CSV data. Circles have fixed radii based on a count value, and drag interactions are enabled via `d3.drag`. Data is loaded from a CSV file using `d3.csv`, and all elements are rendered as SVG.

MMelanieSalignat

Projet final

This force-directed graph visualizes music artist recommendations derived from association-rule mining on a Last.fm-style dataset. Nodes represent artists, while links show recommendation strength, with thicker connections indicating higher co-occurrence support. The visualization is built with d3.v4, using `d3.forceSimulation` for layout and SVG circles and lines for rendering. Hovering a node highlights its immediate connections and applies a semi-transparent “retrait” effect to unrelated nodes, while a custom tooltip shows each artist’s name. Data comes from the included `recommandations.csv` and `artists_tags_count.csv` files.

Projet final

This example visualizes a network of music artist recommendations derived from an association-rule mining dataset, showing how often one artist appears alongside another. A force-directed graph positions nodes for each artist, with links representing recommendation strengths encoded by line opacity and weight. The interface includes a searchable auto-suggest input to highlight a selected artist and dim unrelated nodes, using D3 v4’s `forceSimulation` for layout and SVG circles and lines for rendering. Data comes from CSV files containing artist tags and item-set support counts, with tooltips providing context.

Projet_test3

This example visualizes a network of music artist recommendations, showing connections between artists based on association rule mining. An interactive force-directed graph places artists as nodes, with links representing the strength of their co-occurrence. Hovering over a node highlights it, and a tooltip appears; the code also implements a function to dynamically generate a list of five recommended artists for each selected node. The visualization uses D3.js v4 APIs including `d3.forceSimulation`, `d3.forceLink`, `d3.forceManyBody`, and `d3.forceCenter`, with data loaded from CSV files (`recommandations.csv` and `artists_tags_count.csv`). Artist images and top five tags are integrated from the latter source, enhancing node details.

BBrunoDumas