Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Welcome To Ask or Share your Answers For Others

Categories

0 votes
607 views
in Technique[技术] by (71.8m points)

algorithm - Find the maximally intersecting subset of ranges

If you have a set of ranges, such as the following simple example...

[
    [12, 25], #1
    [14, 27], #2
    [15, 22], #3
    [17, 21], #4
    [20, 65], #5
    [62, 70], #6
    [64, 80]  #7
]

... how do you compute the maximally intersecting subset (not sure quite how to phrase it, but I mean "the subset of ranges which intersects and has the highest cardinality") and determine the degree of intersection (cardinality of ranges in that subset)?

Logically I can work it out, and might be able to translate that to a naive algorithm. Going down the list, we see that 1-5 intersect, and 5-7 intersect, and that #5 intersects both sets.

The result I want is simply the subset, since that gives me the information about the cardinality, and I can easily compute the intersection of the set as long as they all intersect. In the above example, it would be [[14, 27],[15, 22],[12, 25],[17, 21],[20, 65]].

Off the top of my head, I might try converting each range to a graph node, connecting the ones which are intersecting, and finding the largest fully-connected graph.

I was also thinking iteratively to start at the beginning, continue building up a list of intersecting ranges with a running intersection on each to check against—until you hit an element which doesn't intersect, then start a new list. Continue checking each item against the existing intersections. However I'm not sure this is complete.

I could take a stab at implementing something (lang is ruby FWIW), but I would love to hear how others might solve this problem, and what the most efficient and elegant way might be.

Update:

I believe this is a specific case of the Maximum clique problem, which is NP-hard and thus actually difficult. Suggestions for approximations/real-world use would be most appreciated!

See also: http://en.wikipedia.org/wiki/Maximum_clique / Find all complete sub-graphs within a graph

Update 2

Found a nice proof of this problem's NP-hardness and NP-completeness here: http://www.cs.bris.ac.uk/~popa/ipl.pdf

Looks like this is the end of the line then. Sorry folks! I'll work with a good-enough greedy approximation. Thanks.

As said in the answers I don't think that paper describes this problem... we probably have more information here based on the ranges.

See Question&Answers more detail:os

与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
Welcome To Ask or Share your Answers For Others

1 Reply

0 votes
by (71.8m points)

If I understand the problem correctly, it is not an instance of the NP problem described in the paper you linked to. Here is my understanding of the problem, and a polynomial-time solution.

  1. We are given a finite set of ranges of real numbers, say n: [A1, B1], [A2, B2], ..., [An, Bn], where Ai ≤ Bi.

  2. Create a sorted list of the starting and ending points, ordered numerically, indicating whether the point is a starting or ending point.

In your example, this would be: 12+, 14+, 15+, 17+, 20+, 21-, 22-, 25-, 27-, 62+, 64+, 65-, 70-, 80-

  1. Initialize curOverlap and maxOverlap to zero.

  2. Iterate through the list, incrementing curOverlap for each + and decrementing it for each -. Set maxOverlap = max(curOverlap, maxOverlap) on each increment.

To continue your example:
val, cur, max
12, 1, 1
14, 2, 2
15, 3, 3
17, 4, 4
20, 5, 5
21, 4, 5
22, 3, 5
25, 2, 5
27, 1, 5
62, 2, 5
64, 3, 5
65, 2, 5
70, 1, 5
80, 0, 5

The max overlap is 5. You could also store the val associated with the max if you wanted to know where the max overlap occurred. That would give you 20. in this example. It's then trivial to go through the initial set of ranges and find the 5 which include 20.

-edit- If you have repeated values, count the plusses before the minuses for each value so that you include ranges that overlap at a single point.


与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…
OGeek|极客中国-欢迎来到极客的世界,一个免费开放的程序员编程交流平台!开放,进步,分享!让技术改变生活,让极客改变未来! Welcome to OGeek Q&A Community for programmer and developer-Open, Learning and Share
Click Here to Ask a Question

...