4A is applied; FIG. For a better understanding of the present invention and to show more clearly how it may be carried into effect, reference will now be made, by way of example, to the accompanying drawings, which illustrate aspects of embodiments of the present invention and in which: FIG. pruning) involves identifying the symbols with the low efficiency and removing them, while preserving the symbols with the high efficiency values. 8-bits) grouped together. Yet, during the actual compression process byte-strings in the data-set are matched to the longest byte-string/symbol pairs in the static dictionary. Turning to FIG. The dictionaries can be furthermore refined by colocation language in the future. PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362. In accordance with some aspects of the invention, reducing the size of the static dictionary (i.e. Instead, the dictionary supports 120 transforms of dictionary words to support a larger number of matches and find longer matches. There are a number of problems associated with known methods of creating a static dictionary for use in data compression. In accordance with some aspects of the invention, the method also includes: adding child nodes to the plurality of data trees until the combined size of the plurality of the data trees is a predetermined temporary maximum size; and removing binary pattern strings using an evaluation of occurrence count values so as to reduce the combined size of the plurality of data trees down to a predetermined size. Step 3-4 of the method includes pruning the static dictionary, as described above, down to a predetermined temporary pruned size. 3B is a flow chart illustrating the specific steps for tabulating occurrence count values in FIG. WILMINGTON TRUST, NATIONAL ASSOCIATION, DELAWARE, Free format text: Accordingly, for a byte-string of arbitrary length the nodes storing characters near the beginning of the byte-string will inherently have a higher frequency count value than those nodes near the end of the byte-string, since the nodes near the beginning must be traversed to reach the nodes near the end. For example, various aspects of the invention can be embodied in a suitable combination of hardware, software and firmware. Our data set mirrors typical web traffic, covering a wide range of file sizes with small files being more common, which explains the large difference between the weighted and unweighted average. Even for positions where a match exists, a lot of time is spent traversing nodes for the first four bytes since the nodes close to the tree root usually have many children. 3A and 3B illustrate a second method of building a collection of data trees (i.e. Post Syndicated from Felix Hanau original https://blog.cloudflare.com/brotli-compression-using-a-reduced-dictionary/. The hard-wired dictionary used to initialize the data compression algorithm has a big effect on the compression ratio in the early phase of the compression. Cloudflare uses the Google brotli library to dynamically compress web content whenever possible. On the other hand, if the current node is a root node (yes path, step B-8), the method loops back to step B-1.

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