
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.
The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.
This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.
Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.
The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.
An abbreviation of a word follows the form . Below are some examples of word abbreviations:
Assume you have a dictionary and given a word, find whether its abbreviation is unique in the dictionary. A word's abbreviation is unique if no other word from the dictionary has the same abbreviation.
Example:
这道题让我们求独特的单词缩写,但是题目中给的例子不是很清晰,来看下面三种情况:
1. dictionary = {"dear"}, isUnique("door") -> false
2. dictionary = {"door", "door"}, isUnique("door") -> true
3. dictionary = {"dear", "door"}, isUnique("door") -> false
从上面三个例子可以看出,当缩写一致的时候,字典中的单词均和给定单词相同时,返回 true。这里需要用 HashMap 来建立缩写形式和其对应的单词的映射,把所有缩写形式的相同单词放到一个 HashSet 中,然后再判断是否 unique 的时候只需要看给定单词的缩写形式的 HashSet 里面该单词的个数是否和 HashSet 中的元素总数相同,相同的话就是上面的第二种情况,返回 true。需要注意的是由于 HashSet 中不能有重复值,所有上面第二种情况只会有一个 door 存在 HashSet 里,但是并不影响判断结果,参见代码如下:
解法一:
如果我们想省一些空间,也可以不用 HashSet,但如何区分上面的第二和第三种情况呢,在遇到 HashMap 中没有当前缩写形式的时候,将该缩写形式和当前单词建立映射,如果该缩写形式应经存在,那么看如果映射的单词不是当前单词,将映射单词改为空字符串,这样做的原因是,在对于第三种情况 dictionary = {"dear", "door"} 时,遍历 dear 时,建立 d2r 和 dear 的映射,当遍历到 door 的时候,由于 door 和 dear 不同,将映射改为 d2r 和 "" 映射,而对于第二种情况 dictionary = {"door", "door"},保留 d2r 和 door 的映射,那么这样在判断 door 是否 unique 时,就可以区别第二种和第三种情况了,参见代码如下:
解法二:
Github 同步地址:
#288
类似题目:
Two Sum III - Data structure design
Generalized Abbreviation
参考资料:
https://leetcode.com/problems/unique-word-abbreviation/
https://leetcode.com/problems/unique-word-abbreviation/discuss/73133/8-lines-in-C%2B%2B...
https://leetcode.com/problems/unique-word-abbreviation/discuss/73143/Java-Solution-with-One-HashMaplessString-Stringgreater-beats-90-of-Submissions
LeetCode All in One 题目讲解汇总(持续更新中...)
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