**http://en.wikipedia.org/wiki/Bloom_filter**

Hash table A small phone book as a hash table Hashing[edit] The idea of hashing is to distribute the entries (key/value pairs) across an array of buckets. Given a key, the algorithm computes an index that suggests where the entry can be found: index = f(key, array_size) Think Bayes Bayesian Statistics Made Simple by Allen B. Downey Download Think Bayes in PDF. Read Think Bayes in HTML. Order Think Bayes from Amazon.com. Why Bloom filters work the way they do Imagine you’re a programmer who is developing a new web browser. There are many malicious sites on the web, and you want your browser to warn users when they attempt to access dangerous sites. For example, suppose the user attempts to access You’d like a way of checking whether domain is known to be a malicious site. What’s a good way of doing this? An obvious naive way is for your browser to maintain a list or set data structure containing all known malicious domains.

Red–black tree A red–black tree is a data structure which is a type of self-balancing binary search tree. Balance is preserved by painting each node of the tree with one of two colors (typically called 'red' and 'black') in a way that satisfies certain properties, which collectively constrain how unbalanced the tree can become in the worst case. When the tree is modified, the new tree is subsequently rearranged and repainted to restore the coloring properties.

Selection algorithm The simplest case of a selection algorithm is finding the minimum (or maximum) element by iterating through the list, keeping track of the running minimum – the minimum so far – (or maximum) and can be seen as related to the selection sort. Conversely, the hardest case of a selection algorithm is finding the median, and this necessarily takes n/2 storage. In fact, a specialized median-selection algorithm can be used to build a general selection algorithm, as in median of medians. The best-known selection algorithm is quickselect, which is related to quicksort; like quicksort, it has (asymptotically) optimal average performance, but poor worst-case performance, though it can be modified to give optimal worst-case performance as well. Selection by sorting[edit] Rather than sorting the whole list or array, one can instead use partial sorting to select the k smallest or k largest elements.

Operational transformation Operational transformation (OT) is a technology for supporting a range of collaboration functionalities in advanced collaborative software systems. OT was originally invented for consistency maintenance and concurrency control in collaborative editing of plain text documents. Two decades of research has extended its capabilities and expanded its applications to include group undo, locking, conflict resolution, operation notification and compression, group-awareness, HTML/XML and tree-structured document editing, collaborative office productivity tools, application-sharing, and collaborative computer-aided media design tools (see OTFAQ). In 2009 OT was adopted as a core technique behind the collaboration features in Apache Wave and Google Docs.

Heap Example of a complete binary max-heap with node keys being integers from 1 to 100 1. the min-heap property: the value of each node is greater than or equal to the value of its parent, with the minimum-value element at the root. 2. the max-heap property: the value of each node is less than or equal to the value of its parent, with the maximum-value element at the root. Throughout this article the word heap will always refer to a min-heap. Genetic Programming: Evolution of Mona Lisa [EDIT] Added FAQ here: Gallery here: This weekend I decided to play around a bit with genetic programming and put evolution to the test, the test of fine art :-) I created a small program that keeps a string of DNA for polygon rendering. The procedure of the program is quite simple:

Disjoint-set data structure MakeSet creates 8 singletons. After some operations of Union, some sets are grouped together. Find: Determine which subset a particular element is in. This can be used for determining if two elements are in the same subset.Union: Join two subsets into a single subset. In order to define these operations more precisely, some way of representing the sets is needed. One common approach is to select a fixed element of each set, called its representative, to represent the set as a whole. Bitap algorithm The bitap algorithm (also known as the shift-or, shift-and or Baeza-Yates–Gonnet algorithm) is an approximate string matching algorithm. The algorithm tells whether a given text contains a substring which is "approximately equal" to a given pattern, where approximate equality is defined in terms of Levenshtein distance — if the substring and pattern are within a given distance k of each other, then the algorithm considers them equal. The algorithm begins by precomputing a set of bitmasks containing one bit for each element of the pattern. Then it is able to do most of the work with bitwise operations, which are extremely fast. Due to the data structures required by the algorithm, it performs best on patterns less than a constant length (typically the word length of the machine in question), and also prefers inputs over a small alphabet. Exact searching[edit]

Binary search tree A binary search tree of size 9 and depth 3, with 8 at the root. The leaves are not drawn. Binary search trees keep their keys in sorted order, so that lookup and other operations can use the principle of binary search: when looking for a key in a tree (or a place to insert a new key), they traverse the tree from root to leaf, making comparisons to keys stored in the nodes of the tree and deciding, based on the comparison, to continue searching in the left or right subtrees. On average, this means that each comparison allows the operations to skip about half of the tree, so that each lookup, insertion or deletion takes time proportional to the logarithm of the number of items stored in the tree.

Linked list A linked list whose nodes contain two fields: an integer value and a link to the next node. The last node is linked to a terminator used to signify the end of the list. The principal benefit of a linked list over a conventional array is that the list elements can easily be inserted or removed without reallocation or reorganization of the entire structure because the data items need not be stored contiguously in memory or on disk, while an array has to be declared in the source code, before compiling and running the program. Linked lists allow insertion and removal of nodes at any point in the list, and can do so with a constant number of operations if the link previous to the link being added or removed is maintained during list traversal.

Priority queue Operations[edit] A priority queue must at least support the following operations: More advanced implementations may support more complicated operations, such as pull_lowest_priority_element, inspecting the first few highest- or lowest-priority elements, clearing the queue, clearing subsets of the queue, performing a batch insert, merging two or more queues into one, incrementing priority of any element, etc. Similarity to queues[edit] Stacks and queues may be modeled as particular kinds of priority queues. As a reminder, here is how stacks and queues behave:

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