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[LeetCode] 274. H-Index H指数

时间:2018-03-27 10:20:38      阅读:138      评论:0      收藏:0      [点我收藏+]

标签:gpo   遇到   wiki   HERE   量化   pos   最可   sed   index   

Given an array of citations (each citation is a non-negative integer) of a researcher, write a function to compute the researcher‘s h-index.

According to the definition of h-index on Wikipedia: "A scientist has index h if h of his/her N papers have at least h citations each, and the other N − h papers have no more than h citations each."

For example, given citations = [3, 0, 6, 1, 5], which means the researcher has 5 papers in total and each of them had received 3, 0, 6, 1, 5 citations respectively. Since the researcher has 3 papers with at least 3 citations each and the remaining two with no more than 3 citations each, his h-index is 3.

Note: If there are several possible values for h, the maximum one is taken as the h-index.

Credits:
Special thanks to @jianchao.li.fighter for adding this problem and creating all test cases.


H指数(H index)是一个混合量化指标,可用于评估研究人员的学术产出数量与学术产出水平

可以按照如下方法确定某人的H指数:

将其发表的所有SCI论文按被引次数从高到低排序;
从前往后查找排序后的列表,直到某篇论文的序号大于该论文被引次数。所得序号减一即为H指数。

解法1: 先将数组排序,T:O(nlogn), S:O(1)。然后对于每个引用次数,比较大于该引用次数的文章,去引用次数和文章数的最小值,即 Math.min(citations.length-i, citations[i]),并更新 level,取最大值。排好序之后可以用二分查找进行遍历,这样速度会更快,可见:275. H-Index II H指数 II

解法2: Counting sort,T:O(n), S:O(n)。使用一个大小为 n+1 的数组count统计引用数,对于count[i]表示的是引用数为 i 的文章数量。从后往前遍历数组,当满足 count[i] >= i 时,i 就是 h 因子,返回即可,否则返回0。

为什么要从后面开始遍历? 为什么 count[i] >= i 时就返回?

一方面引用数引用数大于 i-1 的数量是i-1及之后的累加,必须从后往前遍历。另一方面,h 因子要求尽可能取最大值,而 h 因子最可能出现最大值的地方在后面,往前值只会越来越小,能尽快返回就尽快返回,所以一遇到 count[i] >= i 就返回。参考:Code_Granker

Java:

public class Solution {  
    public int hIndex(int[] citations) {  
        Arrays.sort(citations);  
        int level = 0;  
        for(int i = 0; i < citations.length; i++)  
            level = Math.max(level,Math.min(citations.length - i,citations[i]));  
        return level;  
    }  
}   

Java:

public class Solution {  
    public int hIndex(int[] citations) {  
        int n = citations.length;  
        int[] count = new int[n + 1];  
        for(int c : citations)  
            if(c >= n) count[n]++;  //当引用数大于等于 n 时,都计入 count[n]中  
            else count[c]++;  
        for(int i = n; i > 0; i--) {  //从后面开始遍历  
            if(count[i] >= i) return i;  
            count[i-1] += count[i];  //引用数大于 i-1 的数量是i-1及之后的累加  
        }  
        return 0;  
    }  
} 

Python:   Counting sort.

class Solution(object):
    def hIndex(self, citations):
        """
        :type citations: List[int]
        :rtype: int
        """
        n = len(citations);
        count = [0] * (n + 1)
        for x in citations:
            # Put all x >= n in the same bucket.
            if x >= n:
                count[n] += 1
            else:
                count[x] += 1

        h = 0
        for i in reversed(xrange(0, n + 1)):
            h += count[i]
            if h >= i:
                return i
        return h 

Python: T: O(nlogn) O: O(1)

class Solution2(object):
    def hIndex(self, citations):
        """
        :type citations: List[int]
        :rtype: int
        """
        citations.sort(reverse=True)
        h = 0
        for x in citations:
            if x >= h + 1:
                h += 1
            else:
                break
        return h

Python: T: O(nlogn) O: O(n) 

class Solution3(object):
    def hIndex(self, citations):
        """
        :type citations: List[int]
        :rtype: int
        """
        return sum(x >= i + 1 for i, x in enumerate(sorted(citations, reverse=True))) 

Python:

class Solution(object):
    def hIndex(self, citations):
        """
        :type citations: List[int]
        :rtype: int
        """
        if not citations: return 0
        return max([min(i + 1, c) for i, c in enumerate(sorted(citations, reverse=True))])  

C++:

class Solution {
public:
    int hIndex(vector<int>& citations) {
        sort(citations.begin(), citations.end(), greater<int>());
        for (int i = 0; i < citations.size(); ++i) {
            if (i >= citations[i]) return i;
        }
        return citations.size();
    }
}; 

 

类似题目:

[LeetCode] 275. H-Index II H指数 II 

 

[LeetCode] 274. H-Index H指数

标签:gpo   遇到   wiki   HERE   量化   pos   最可   sed   index   

原文地址:https://www.cnblogs.com/lightwindy/p/8655160.html

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