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h-index explained and leetcode 274 solution in python
the h-index is a metric used to evaluate the cumulative impact and significance of a researcher's publications. it represents the maximum value of 'h' such that the given researcher/author has published at least 'h' papers that have each been cited at least 'h' times. in simpler terms, a scientist with an index of `h` has published `h` papers each of which has been cited in other papers at least `h` times.
this tutorial will break down the concept of the h-index, its practical significance, the algorithm for calculating it, and a python solution to the leetcode problem 274 (h-index).
**understanding the h-index**
* **core idea:** the h-index aims to balance the number of publications and the number of citations per publication. it discourages focusing solely on publishing a large number of less influential papers or only publishing a few highly influential papers. a good h-index generally indicates consistent production of impactful research.
* **example 1:**
* a researcher has the following publications and citations:
* paper 1: 10 citations
* paper 2: 8 citations
* paper 3: 5 citations
* paper 4: 4 citations
* paper 5: 3 citations
* in this case, the h-index is 4. why?
* the researcher has 4 papers with at least 4 citations each (10, 8, 5, and 4).
* they do *not* have 5 papers with at least 5 citations each (the 5th paper only has 3 citations).
* **example 2:**
* a researcher has the following publications and citations:
* paper 1: 25 citations
* paper 2: 8 citations
* paper 3: 5 citations
* paper 4: 3 citations
* paper 5: 3 citations
* here, the h-index is 3.
* the researcher has 3 papers with at least 3 citations each (25, 8, and 5).
* they do *not* have 4 papers with at least 4 citations each (the 4th paper only has 3 citations).
* **practical significance:**
* ** ...
#HIndex #LeetCode #americandefense
H index
LeetCode
problem 274
arrays
strings
Python
algorithm
coding challenge
data structures
research metrics
programming
interview preparation
computational complexity
academic performance
solution approach
the h-index is a metric used to evaluate the cumulative impact and significance of a researcher's publications. it represents the maximum value of 'h' such that the given researcher/author has published at least 'h' papers that have each been cited at least 'h' times. in simpler terms, a scientist with an index of `h` has published `h` papers each of which has been cited in other papers at least `h` times.
this tutorial will break down the concept of the h-index, its practical significance, the algorithm for calculating it, and a python solution to the leetcode problem 274 (h-index).
**understanding the h-index**
* **core idea:** the h-index aims to balance the number of publications and the number of citations per publication. it discourages focusing solely on publishing a large number of less influential papers or only publishing a few highly influential papers. a good h-index generally indicates consistent production of impactful research.
* **example 1:**
* a researcher has the following publications and citations:
* paper 1: 10 citations
* paper 2: 8 citations
* paper 3: 5 citations
* paper 4: 4 citations
* paper 5: 3 citations
* in this case, the h-index is 4. why?
* the researcher has 4 papers with at least 4 citations each (10, 8, 5, and 4).
* they do *not* have 5 papers with at least 5 citations each (the 5th paper only has 3 citations).
* **example 2:**
* a researcher has the following publications and citations:
* paper 1: 25 citations
* paper 2: 8 citations
* paper 3: 5 citations
* paper 4: 3 citations
* paper 5: 3 citations
* here, the h-index is 3.
* the researcher has 3 papers with at least 3 citations each (25, 8, and 5).
* they do *not* have 4 papers with at least 4 citations each (the 4th paper only has 3 citations).
* **practical significance:**
* ** ...
#HIndex #LeetCode #americandefense
H index
LeetCode
problem 274
arrays
strings
Python
algorithm
coding challenge
data structures
research metrics
programming
interview preparation
computational complexity
academic performance
solution approach