CS276: Information Retrieval and Web Search Pandu Nayak and Prabhakar Raghavan Lecture 3: Dictionaries and tolerant retrieval. Ch. 2. Recap of the previous lecture. The type/token distinction Terms are normalized types put in the dictionary Tokenization problems:

ByChapter 2. The Complexity of Algorithms and the Lower Bounds of Problems. The goodness of an algorithm . Time complexity (more important) Space complexity For a parallel algorithm : time-processor product For a VLSI circuit : area-time (AT, AT 2 ). Measure the goodness of an algorithm.

ByDepartment of Information Technology. Computer Programming & Problem Solving Ch 9 Dynamic Data Structures. Outline. Introduction Self-Referential Structures Dynamic Memory Allocation Linked Lists Stacks Queues Trees. Objectives. In this chapter, you will learn:

ByCSC 213 – Large Scale Programming. Lecture 22: The Rolling Stones, Masters of the Balanced Tree. Red-Black Tree Properties. Root Property: Root node painted black External Property: Leaves are painted black Internal Property: Red node s’ children are black

ByParallelism is Everywhere – So How Do We Make It Accessible?. Daniel Ernst Department of Computer Science The University of Wisconsin – Eau Claire. A Little Background …. “Grew Up” (Graduate School) in Computer Architecture Efficient, fast, low-power processors (2 ISCA, 1 MICRO papers, +)

ByHwajung Lee. ITEC452 Distributed Computing Lecture 10 Coordination Algorithms. Leader Election. Let G = (V,E) define the network topology. Each process i has a variable L(i) that defines the leader . i,j V i,j are non-faulty :: L(i) V and

ByCSE332: Data Abstractions Lecture 26: Minimum Spanning Trees. Dan Grossman Spring 2010. “Scheduling note”. “We now return to our interrupted program” on graphs Last “graph lecture” was lecture 17 Shortest-path problem Dijkstra’s algorithm for graphs with non-negative weights

ByBinary Search Trees. If we want to perform a large number of searches in a particular list of items, it can be worthwhile to arrange these items in a binary search tree to facilitate the subsequent searches.

ByDeletion algorithm – Phase 2: Remove node or replace its with successor. TreeNode<T> deleteNode(TreeNode<T> n) { // Returns a reference to a node which replaced n. // Algorithm note: There are four cases to consider: // 1. The n is a leaf. // 2. The n has no left child.

ByAVL Tree Rotations. About Rotations. A right rotation can be done on any node having a left child. A left rotation can be done on any node having a right child. A rotation always preserves the BST invariants. It might or might not decrease the height of the subtree. Parent. Parent.

ByCS 132 Spring 2008 Chapter 11. Binary Trees p. 631-666. Jill’s Pizza Shop. Owner Jill Manager Chef Brad Carl

ByB+ Tree. By Li Wen CS157B Professor: Sin-Min Lee What is a B+ Tree Searching Insertion Deletion. What is a B+ Tree. Definition and benefits of a B+Tree

ByPurely Functional Worst Case Constant Time Catenable Sorted Lists Gerth Stølting Brodal University of Aarhus Joint work with Christos Makris Kostas Tsichlas University of Patras. ESA’06, Zürich, Switzerland, September 13, 2006. This talk. Catenable Sorted Lists. Insert( T , x )

By308-203A Introduction to Computing II Lecture 9: Binary Search/Trees. Fall Session 2000. Binary Search. Goal : Find a particular element in a sorted array Solution : Break the data to be searched in two by looking at the middle element

ByIntroduction Data structure AVL tree balance condition AVL node level AVL rotations Choosing the rotation Performing a balanced insertion Outputting data Testing and results. AVL Balanced Trees.

ByAlgorithms and Data Structures CMPSC 465. Adam Smith. L ECTURES 22-23 Binary Search Trees. Heaps: Review. Heap-leap-jeep-creep(A): A.heap -size = 0 For i =1 to len (A) t mp = A[ i ] Heap-Insert( A,tmp ) For i = len (A) down to 1 tmp = Heap-Extract-Max(A) A[ i ]= tmp

ByChapter 12&13: Binary Search Trees (BSTs). Overview: Definition of dynamic sets Operations on dynamic sets Definition of BST Examples of balanced and unbalanced BSTs support dynamic-set operations T(n) proportional to height of tree Extensions, like Red-Black trees, ensure balance.

ByAVL TREES. By Asami Enomoto CS 146. AVL Tree is…. named after A delson- V elskii and L andis the first dynamically balanced trees to be propose Binary search tree with balance condition in which the sub-trees of each node can differ by at most 1 in their height.

ByDecision Trees & Rule-based AI. Decision Tree. Advantages Fast and easy to implement, Simple to understand Modular, Re-usable Can be learned can be constructed dynamically from observations and actions in game, we will discuss this further in a future topic called ‘Learning’).

ByAVL Trees. Joe Meehean. Problem. BST efficiency relies on height lookup, insert, delete: O(height) a balanced tree has the smallest height We can balance an unbalanced tree DSW expensive How can we ensure that our BST stays balanced? after inserts and deletes. AVL Trees.

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