Projet 4

Projet 4

This network visualization maps music artist recommendations, showing associations between bands and solo acts. It displays artists as nodes, with connections and support values indicating the strength of their association. The visualization uses a force-directed simulation, `d3.forceSimulation` in the D3.js framework, to position nodes and draw links between them. Data is loaded from `recommandations.csv`, which includes the antecedent, consequence, and item-set support for each recommendation pair. The visualization also includes an interactive autocomplete feature for searching artists.

94% 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.

RRomyRatolojanahary

92% match

Projet 3

This visualization displays song recommendations as a directed network graph, where each node represents a musical artist and each edge connects an antecedent artist to a consequent artist, with edge thickness or weight reflecting the support count from the dataset. Using D3 version 4's force-directed layout via `d3.forceSimulation`, the graph arranges nodes spatially to reveal clusters of related musicians. The interface includes an interactive search box that filters and highlights specific artists from a predefined list, while a tooltip provides details on hover. The underlying data comes from a CSV file of association rules derived from user tagging patterns, rendered as an SVG with custom styling for nodes and links.

91% match

Projet 2

This visualization shows a force-directed network of music artists and their associations, mapping relationships derived from an association-rule mining dataset where nodes represent artists and links indicate co-occurrence strength. The graph uses `d3.forceSimulation` with collision and link forces to position nodes, with circle size encoding node degree and line opacity reflecting link weight. Hovering a node highlights its connections, and the code includes an autocomplete search feature that filters the network. Data is loaded from CSV files containing artist tags and recommendation pairs, rendered as SVG elements with tooltips for interactivity.

91% match

Projet : Artists recommendation

This visualization presents a force-directed network of music artist recommendations, derived from association rule mining in `recommandations.csv`. Nodes represent individual artists, while weighted links depict the strength of their co-occurrence in recommendation rules. The network uses a physical simulation engine, combining `d3.forceSimulation` with `d3.forceLink`, `d3.forceManyBody`, and `d3.forceCenter` forces to arrange the graph. Upon hovering over a node, the code highlights that artist and all directly recommended artists by increasing their radius and changing their color, with a custom tooltip displaying the artist's name. The visualization is rendered as an SVG using D3 v4.

Projet final

This visualization shows a network of music artists, with nodes connected by association rules derived from item-set support values. It presents a force-directed graph where each circle represents an artist, and links indicate shared listener preferences or recommendations between them, with node size and link strength reflecting the support counts. The implementation uses D3 v4’s `d3.forceSimulation` for layout, rendering nodes and links as SVG circles and lines. Hovering highlights a node, dims unrelated connections, and displays a tooltip with the artist’s name and support value, based on data from CSV files containing artist tags and recommendation counts.

Projet final

This network graph shows music artist recommendations derived from association rule mining. Each node is an artist, and a directed edge connects an antecedent to a consequence. The thickness of a link encodes the support count for that rule, as seen in the `recommandations.csv` file. Artists are colored or sized by tag counts from `artists_tags_count.csv`. The visualization uses D3.js v4's force-directed layout to position nodes, with SVG paths and circles rendering the links and nodes. Hovering on a node triggers a brush effect that highlights connected nodes while dimming the rest.

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.