Search Results for "indexing"

A really fast static spatial index for 2D points and rectangles in JavaScript. An efficient implementation of the packed Hilbert R-tree algorithm. Enables fast spatial queries on a very large number of objects (e.g. millions), which is very useful in maps, data visualizations and computational geometry algorithms.

RBush is a high-performance JavaScript library for 2D spatial indexing of points and rectangles. It's based on an optimized R-tree data structure with bulk insertion support. Spatial index is a special data structure for points and rectangles that allows you to perform queries like "all items within this bounding box" very efficiently (e.g. hundreds of times faster than looping over all items). It's most commonly used in maps and data visualizations.

...Skip the tedious work of setting up test data, and dive straight into practicing algorithms. Heaps and BSTs (binary search trees) are also supported. Binarytree supports another representation which is more compact but without the indexing properties. Traverse trees using different algorithms.

This library implements several locality sensitive hashing(LSH) based algorithms, including indexing data structure for high dimensional spaces and metric spaces, sketch constructions and set embedding algorithms.

Application provide indexing and searching capability using Inverted File & TVSM methods. Also provide native integration with UNIX based indexing service also GoogleBase & YouTube search via Atom feeds.

Locality Sensitive Hashing is an improved indexing method for high dimensional data. lshtools provides indexing with LSH and an intelligent non supervised subsampling strategy using this indexing method.

This project intends to create an indexing search engine, for knowledge management. The primary object is to apply an information retrieval core. And implement a knowledge data discovery theory such as data mining algorithm, text mining.

reputron is a knowledge extraction engine platform that covers all aspect of text mining, relevance, indexing and querying on a corpus of text documents.