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https://github.com/piotrbaczek/zipfsong

Solution to zipfsong problem on Spotify - as far as I've seen my solution is the most effective
https://github.com/piotrbaczek/zipfsong

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Solution to zipfsong problem on Spotify - as far as I've seen my solution is the most effective

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zipfsong

========



Solution to zipfsong problem on Spotify - as far as I've seen my solution is the most effective



Zipf’s Songs

Problem ID: zipfsong



Your slightly pointy-bearded boss has assigned you to write software

to find the best songs from different music albums. And the

software should be finished in an hour. But don’t panic, you don’t

have to solve the problem of writing an AI with good taste. At

your disposal is the impeccable taste of a vast horde of long-tailed

monkeys. Well, at least almost. The monkeys are not very communicative

(or rather, you’re not sure which song “Ook!” is supposed

to refer to) so you can’t ask them which songs are the best.

What you can do however is to look at which songs the monkeys

have listened to and use this information to deduce which songs

are the best.

At first, you figure that the most listened to songs must be the

best songs. However, you quickly realize that this approach is

flawed. Even if all songs of the album are equally good, the early songs are more likely to be listened to more

often than the later ones, because monkeys will tend to start listening to the first song, listen for a few songs and

then, when their fickle ears start craving something else, stop listening. Instead, if all songs are equal, you expect

that their play frequencies should follow Zipf’s Law.

Zipf’s Law is an empirical law originally formulated about word frequencies in natural languages, but it has

been observed that many natural phenomena, such as population sizes and incomes, approximately follow the

same law. It predicts that the relative frequency of the i’th most common object (in this case, a song) should be

proportional to 1/i.

To illustrate this in our setting, suppose we have an album where all songs are equally good. Then by Zipf’s

Law, you expect that the first song is listened to twice as often as the second song, and more generally that the

first song is listened to i times as often as the i’th song. When some songs are better than others, those will be

listened to more often than predicted by Zipf’s Law, and those are the songs your program should select as the

good songs. Specifically, suppose that song i has been played fi times but that Zipf’s Law predicts that it would

have been played zi times. Then you define the quality of song i to be qi = fi/zi. Your software should select the

songs with the highest values of qi.

Input

The first line of input contains two integers n and m (1  n  50 000, 1  m  n), the number of songs on the

album, and the number of songs to select. Then follow n lines. The i’th of these lines contains an integer fi and

string si, where 0  fi  1012 is the number of times the i’th song was listened to, and si is the name of the song.

Each song name is at most 30 characters long and consists only of the characters ‘a’-‘z’, ‘0’-‘9’, and underscore

(‘ ’).



Output



Output a list of the m songs with the highest quality qi, in decreasing order of quality. If two songs have the same

quality, give precedence to the one appearing first on the album (presumably there was a reason for the producers

to put that song before the other).



Sample input 1 Sample output 1



4 2

30 one

30 two

15 three

25 four

four

two



Sample input 2 Sample output 2



15 3

197812 re_hash

78906 5_4

189518 tomorrow_comes_today

39453 new_genious

210492 clint_eastwood

26302 man_research

22544 punk

19727 sound_check

17535 double_bass

18782 rock_the_house

198189 19_2000

13151 latin_simone

12139 starshine

11272 slow_country

10521 m1_a1

19_2000

clint_eastwood

tomorrow_comes_today