Essentials of MIS (13th Edition)
13th Edition
ISBN: 9780134802756
Author: Kenneth C. Laudon, Jane Laudon
Publisher: PEARSON
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Expert Solution & Answer
Chapter 2, Problem 13CSQ
Explanation of Solution
Factors of people involved in internal corporate social networks:
- The companies don’t include social networking sites because they assume that employees may ignore the work by chatting with friends and family.
- Nearly, 22% of people believe that
information systems or social networking can be used in improving their careers. - The employees must follow guidelines and undergo training to use information systems like social networking.
Factors of organization involved in internal corporate social networks:
- According to certain analysis and surveys, social networking cannot be used for aggregating and developing the companies...
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Students have asked these similar questions
Design a dynamic programming algorithm for the Longest Common Subsequence problem de-
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Input: Two strings x = x1x2 xm and y = Y1Y2... Yn
Output: The length of the longest subsequence that is common to both x and y.
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The algorithm must take O(m n) time. You must also write and explain the recurrence.
(I want the largest k such that there are 1 ≤ i₁ < ... < ik ≤ m and 1 ≤ j₁ < ... < jk ≤ n such that
Xi₁ Xi2 Xik = Yj1Yj2 ··· Yjk)
Example 1:
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Output: 6 ('ghnost' is the longest common subsequence to both strings)
Example 2:
Input: x = 'ahshku' and y = ‘asu'
Output: 3 ('asu' is the longest common subsequence to both strings)
Design a dynamic programming algorithm for the problem described below
Input: A list of numbers A = = [a1,..., an].
Output: A contiguous subsequence of numbers with the maximum sum.
The algorithm must take O(n) time. You must also write and explain the recurrence.
(I am looking for an i ≥ 1 and k ≥ 0 such that a + ai+1 + ···ai+k has the largest possible sum among all
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Example 1:
Input: A[5, 15, -30, 10, -5, 40, 10].
Output: [10, 5, 40, 10]
Example 2:
Input: A = [7, 5, 7, 4, -20, 6, 9, 3, -4, -8, 4]
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Design a dynamic programming algorithm for the Longest Increasing Subsequence problem
described below:
Input: A sequence of n integers
Output: The length of the longest increasing subsequence among these integers.
The algorithm must take O(n²) time. You must also write and explain the recurrence.
Example 1:
Input: [5, 3, 6, 8, 4, 6, 2, 7, 9, 5]
Output: 5 ([3, 4, 6, 7, 9])
Example 2:
Input: [12, 42, 66, 73, 234, 7, 543, 16]
Output: 6 ([42, 66, 73, 234, 543])
Chapter 2 Solutions
Essentials of MIS (13th Edition)
Ch. 2.2 - What Kinds of systems are illustrated in this case...Ch. 2.2 - Prob. 2CQ1Ch. 2.2 - Prob. 3CQ1Ch. 2.2 - Prob. 4CQ1Ch. 2.3 - Prob. 1CQ2Ch. 2.3 - Prob. 2CQ2Ch. 2.3 - Prob. 3CQ2Ch. 2 - Prob. 1IQCh. 2 - Prob. 2IQCh. 2 - Prob. 3IQ
Ch. 2 - Prob. 4IQCh. 2 - Prob. 5IQCh. 2 - Prob. 6IQCh. 2 - Prob. 1RQCh. 2 - Prob. 2RQCh. 2 - Prob. 3RQCh. 2 - Prob. 4RQCh. 2 - Prob. 5DQCh. 2 - Prob. 6DQCh. 2 - Prob. 7DQCh. 2 - Prob. 8HMPCh. 2 - Prob. 9HMPCh. 2 - Prob. 12CTPCh. 2 - Prob. 13CSQCh. 2 - Prob. 14CSQCh. 2 - Prob. 15CSQCh. 2 - Prob. 16MLMCh. 2 - Prob. 17MLM
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