Data Mining

Data Mining

A network visualization maps movie recommendations from a CSV dataset, showing connections between films based on association-rule mining. Users can click or hover over nodes to highlight related movies, with a tooltip displaying the film title and a zoom feature for closer inspection. The code uses d3.forceSimulation for layout, d3.csv for data loading, and SVG circles and lines for rendering, with d3.zoom enabling pan and zoom interactions.

92% match

Films_mal_notes

This visualization displays a network of film recommendations derived from association rule mining, where nodes represent movie titles and links indicate that one movie is frequently purchased alongside another. Node color encodes the film title, while the link data itself includes an item set support value, though it is not visually encoded in the displayed stroke width. The graph is laid out using the D3.js force simulation API, specifically `d3.forceSimulation` with `d3.forceLink` and `d3.forceManyBody`, and rendered as an SVG with draggable nodes. The data comes from the `recommandations.csv` file, which lists pairwise antecedent–consequence movie relationships.

RRomyRatolojanahary

88% match

Data Mining

This interactive visualization maps the interconnectedness of films, showing how a single movie like *2001: A Space Odyssey* links to a vast network of over one hundred related titles. The primary display uses a force-directed graph layout via D3.js v4’s `forceSimulation` to position the nodes of the recommendation network. A separate chart reveals the frequency of genre pairs, drawing on the `genres.csv` dataset. Data is rendered as SVG, with the dataset loaded from external CSV files in a custom script.

87% match

Projet 4

This visualization displays a network of recommended music artists based on association rule mining. The force-directed graph shows artist nodes connected by links, where the strength of each connection represents the support value from the dataset. Using D3 v4, the layout employs a force simulation to position nodes, with link opacity reflecting relationship strength. The data comes from a CSV file containing antecedent-consequence pairs with support counts, and the interactive visualization also includes a searchable autocomplete feature for finding specific artists in the network.

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 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.

Untitled

This interactive network graph visualizes connections between movies, with each node representing a film and links showing relationships between them. The visualization uses d3.v3 to render the force-directed layout, with nodes colored and sized by their calculated score and level values. Clicking a node displays additional movie details including title, cast, director, and cover image in a side panel. The implementation reads from a movie-network.json data file and uses d3.forceSimulation for the physics-based node positioning and link rendering.

NNathannous

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.