{"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}
引用次数: 0
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.