Question

在设计像字典这样的字典以储存字面时,TRIIE是否是最推荐的数据结构? 任何其他改进时间或记忆性能的办法?

我认为,如果不发生碰撞,那么记忆要求就会变得不好,因为重复的话:在重叠、重叠、重叠、重叠、重叠和重叠的情况下,所有这些都占据了独一无二的储存,而我们可以在三角地分享空间。

EDIT: 感谢@Moron,并感谢你所作的非常有益的回答。我同意——生成散射钥匙是O(n) ,也是一种TRIE搜索。然而,由于链条加起来,随着时间的推移,而对于跨国激进党来说,这种情况不会发生。我仍然关切的是,对于跨国激进党的每一个节点,我需要保持一个点,如果独裁者的规模很小的话,可能会对事情进行打击。

Answer 1

http://en.wikipedia.org/wiki/Directed_acyclic_word_graph”rel=“nofollow noreferer” 参考书目: 记忆的消耗量基本是微不足道的,但记忆的使用较好,根据维基,对于联合国来说,记忆的消耗量远远低于微不足道。

时间是明智的,好像是微不足道的,可能比过去好。不能确定你去奥(logn)的时间。如果是所搜索的字长,那就应当是O(n)。

Answer 2

三个小组拥有以下优势:

Looking up data in a trie is faster in the worst case, O(m) time, compared to an imperfect hash table. An imperfect hash table can have key collisions. A key collision is the hash function mapping of different keys to the same position in a hash table. The worst-case lookup speed in an imperfect hash table is O(N) time, but far more typically is O(1), with O(m) time spent evaluating the hash.
There are no collisions of different keys in a trie.
Buckets in a trie which are analogous to hash table buckets that store key collisions are only necessary if a single key is associated with more than one value.
There is no need to provide a hash function or to change hash functions as more keys are added to a trie.
A trie can provide an alphabetical ordering of the entries by key.

特里斯有以下缺点:

Tries can be slower in some cases than hash tables for looking up data, especially if the data is directly accessed on a hard disk drive or some other secondary storage device where the random access time is high compared to main memory.
It is not easy to represent all keys as strings, such as floating point numbers - a straightforward encoding using the bitstring of their encoding leads to long chains and prefixes that are not particularly meaningful.

如果这些缺陷是你能够生活的东西,我建议说这三重。

资料来源:

Answer 3

我猜想的是,这是一个大问题? 或许可以尝试看看一看一盘旋过滤器?

http://en.wikipedia.org/wiki/Bloom_filter

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