{"title":"多流字压缩算法","authors":"Emir Öztürk Altan Mesut, B. Diri","doi":"10.1109/UBMK.2017.8093552","DOIUrl":null,"url":null,"abstract":"In this article, we present a novel word-based lossless compression algorithm for text files which uses a semi-static model. We named our algorithm as Multi-stream Word-based Compression Algorithm (MWCA), because it stores the compressed forms of the words in three individual streams depending on their frequencies in the text. It also stores two dictionaries and a bit vector as a side information. In our experiments MWCA obtains compression ratio over 3,23 bpc on average and 2,88 bpc on files larger than 50 MB. If a variable length encoder like Huffman Coding is used after MWCA, given ratios will reduce to 2,63 and 2,44 bpc respectively. With the advantage of its multi-stream structure MWCA could become a good solution especially for storing and searching big text data.","PeriodicalId":201903,"journal":{"name":"2017 International Conference on Computer Science and Engineering (UBMK)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-stream word-based compression algorithm\",\"authors\":\"Emir Öztürk Altan Mesut, B. Diri\",\"doi\":\"10.1109/UBMK.2017.8093552\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this article, we present a novel word-based lossless compression algorithm for text files which uses a semi-static model. We named our algorithm as Multi-stream Word-based Compression Algorithm (MWCA), because it stores the compressed forms of the words in three individual streams depending on their frequencies in the text. It also stores two dictionaries and a bit vector as a side information. In our experiments MWCA obtains compression ratio over 3,23 bpc on average and 2,88 bpc on files larger than 50 MB. If a variable length encoder like Huffman Coding is used after MWCA, given ratios will reduce to 2,63 and 2,44 bpc respectively. With the advantage of its multi-stream structure MWCA could become a good solution especially for storing and searching big text data.\",\"PeriodicalId\":201903,\"journal\":{\"name\":\"2017 International Conference on Computer Science and Engineering (UBMK)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computer Science and Engineering (UBMK)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UBMK.2017.8093552\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK.2017.8093552","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this article, we present a novel word-based lossless compression algorithm for text files which uses a semi-static model. We named our algorithm as Multi-stream Word-based Compression Algorithm (MWCA), because it stores the compressed forms of the words in three individual streams depending on their frequencies in the text. It also stores two dictionaries and a bit vector as a side information. In our experiments MWCA obtains compression ratio over 3,23 bpc on average and 2,88 bpc on files larger than 50 MB. If a variable length encoder like Huffman Coding is used after MWCA, given ratios will reduce to 2,63 and 2,44 bpc respectively. With the advantage of its multi-stream structure MWCA could become a good solution especially for storing and searching big text data.