1257. Smallest Common Region π
Description
You are given some lists of regions
where the first region of each list directly contains all other regions in that list.
If a region x
contains a region y
directly, and region y
contains region z
directly, then region x
is said to contain region z
indirectly. Note that region x
also indirectly contains all regions indirectly containd in y
.
Naturally, if a region x
contains (either directly or indirectly) another region y
, then x
is bigger than or equal to y
in size. Also, by definition, a region x
contains itself.
Given two regions: region1
and region2
, return the smallest region that contains both of them.
It is guaranteed the smallest region exists.
Example 1:
Input: regions = [["Earth","North America","South America"], ["North America","United States","Canada"], ["United States","New York","Boston"], ["Canada","Ontario","Quebec"], ["South America","Brazil"]], region1 = "Quebec", region2 = "New York" Output: "North America"
Example 2:
Input: regions = [["Earth", "North America", "South America"],["North America", "United States", "Canada"],["United States", "New York", "Boston"],["Canada", "Ontario", "Quebec"],["South America", "Brazil"]], region1 = "Canada", region2 = "South America" Output: "Earth"
Constraints:
2 <= regions.length <= 104
2 <= regions[i].length <= 20
1 <= regions[i][j].length, region1.length, region2.length <= 20
region1 != region2
regions[i][j]
,region1
, andregion2
consist of English letters.- The input is generated such that there exists a region which contains all the other regions, either directly or indirectly.
- A region cannot be directly contained in more than one region.
Solutions
Solution 1: Hash Table
We can use a hash table \(\textit{g}\) to store the parent region of each region. Then, starting from \(\textit{region1}\), we keep moving upwards to find all its parent regions until the root region, and store these regions in the set \(\textit{s}\). Next, starting from \(\textit{region2}\), we keep moving upwards to find the first region that is in the set \(\textit{s}\), which is the smallest common region.
The time complexity is \(O(n)\), and the space complexity is \(O(n)\). Where \(n\) is the length of the region list \(\textit{regions}\).
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