PROGRAMMING:Hot topics on Sina Weibo
Sina Weibo can embed "topic" in the speech, that is, the topic text in the speech can be written between a pair of "#" to generate a topic link. Click the link to see how many people are discussing the same or similar topics with themselves. Sina Weibo will also update the list of hot topics at any time, and put the most popular topics in an eye-catching position to recommend your attention.
This topic requires the implementation of a simplified hot topic recommendation function, parsing topics from a large number of English (because Chinese word segmentation processing is more troublesome) microblogs, and finding the topics mentioned by the most microblogs.
###Input format:
Input Description: input first gives a positive integer $$n $$($$Le 10 ^ 5 $$), then $$n $$lines, each line gives an English microblog, the length of which is no more than 140 characters. Any content contained in a pair of recent ones is considered to be a topic, and the input guarantees that the two appear in pairs.
###Output format:
The first line outputs the topics mentioned by the most microblogs, and the second line outputs the number of microblogs mentioned. If such topics are not unique, output the topic with the smallest alphabetical order, and output 'and K more...' in the third line, where 'k' is the number of other hot topics. The input ensures that at least one topic exists.
Note: the two topics are considered to be the same. If you remove all the symbols of non English letters and numbers and ignore the case distinction, they are the same string; At the same time, they have exactly the same participle. In addition to the first letter in upper case, only lowercase English letters and numbers are reserved, and a space is used to separate the words in the original text.
###Input example:
```in
four
This is a #test of topic#.
Another #Test of topic.#
This is a #Hot# #Hot# topic
Another #hot!# # Hot# topic
```
###Output example:
```out
Hot
two
And 1 more ...
```
answer：If there is no answer, please comment
This topic requires the implementation of a simplified hot topic recommendation function, parsing topics from a large number of English (because Chinese word segmentation processing is more troublesome) microblogs, and finding the topics mentioned by the most microblogs.
###Input format:
Input Description: input first gives a positive integer $$n $$($$Le 10 ^ 5 $$), then $$n $$lines, each line gives an English microblog, the length of which is no more than 140 characters. Any content contained in a pair of recent ones is considered to be a topic, and the input guarantees that the two appear in pairs.
###Output format:
The first line outputs the topics mentioned by the most microblogs, and the second line outputs the number of microblogs mentioned. If such topics are not unique, output the topic with the smallest alphabetical order, and output 'and K more...' in the third line, where 'k' is the number of other hot topics. The input ensures that at least one topic exists.
Note: the two topics are considered to be the same. If you remove all the symbols of non English letters and numbers and ignore the case distinction, they are the same string; At the same time, they have exactly the same participle. In addition to the first letter in upper case, only lowercase English letters and numbers are reserved, and a space is used to separate the words in the original text.
###Input example:
```in
four
This is a #test of topic#.
Another #Test of topic.#
This is a #Hot# #Hot# topic
Another #hot!# # Hot# topic
```
###Output example:
```out
Hot
two
And 1 more ...
```
answer：If there is no answer, please comment