因为理论 编码员依靠不断更新的“字典”,其编码结果取决于历史(从输入数据得出到目前文号的所有字典代码),因此不可能跳到某个地点,开始编码,而不必首先对以前的所有数据进行脱节。

我认为,你只能使用一种流体分解器,这种蒸气排放会减少数据,因为它没有等待整个档案被压缩。 这将节省执行时间,但节省记忆。

第二项建议是将Huffman编成英文字,并忘记关于《刑法》部分的内容。 每个英文字都绘制成独一无二的无固定代码。

Finally, @SHODAN gave the most sensible suggestion, which is to index the files, compress the index and bundle with the compressed text files. To do a search, decompress just the index file and look up the words. This is in fact an improvement over doing the Huffman coding on words - once you found the frequency of words (in order to assign the prefix code optimally), you have already built the index, so you can keep the index for searching.

Searching for text in compressed files can be faster than searching for the same thing in uncompressed text files.

一种压缩技术 我看到,为了迅速搜寻而牺牲了一些空间:

• maintain a dictionary with 2^16 entries of every word in the text. Reserve the first 256 entries for literal bytes, in case you come upon a word that isn t in the dictionary -- even though many large texts have fewer than 32,000 unique words, so they never need to use those literal bytes.
• Compress the original text by substituting the 16-bit dictionary index for each word.
• (optional) In the normal case that two words are separated by a single space character, discard that space character; otherwise put all the bytes in the string between words into the dictionary as a special "word" (for example, ". " and ", " and " ") tagged with the "no default spaces" attribute, and then "compress" those strings by replacing them with the corresponding dictionary index.
• Search for words or phrases by compressing the phrase in the same way, and searching for the compressed string of bytes in the compressed text in exactly the same way you would search for the original string in the original text.

尤其是,寻找一个词通常会减少对压缩案文中16个轨道指数的比较,该指数比在原始案文中寻找该词更快。

• each comparison requires comparing fewer bytes -- 2, rather than however many bytes were in that word, and
• we re doing fewer comparisons, because the compressed file is shorter.

Some kinds of regular expressions can be translated to another regular expression that directly finds items in the compressed file (and also perhaps also finds a few false positives). Such a search also does fewer comparisons than using the original regular expression on the original text file, because the compressed file is shorter, but typically each regular expression comparison requires more work, so it may or may not be faster than the original regex operating on the original text.

(原则上,如上所述,你可以将固定的16轨代码替换成可变的Huffman先令代码,因此压缩文档将减少,但处理这些档案的软件将略为缓慢和复杂。)

对于更先进的技术,你可以研究