{"title":"BWT Tunnel Planning is Hard But Manageable","authors":"Uwe Baier, K. Dede","doi":"10.1109/DCC.2019.00022","DOIUrl":null,"url":null,"abstract":"The Burrows-Wheeler transform is a well known and useful text transformation used for both data compression and text indexing. Recently, a new technique called \"tunneling\" was presented, improving compression rates of BWT compressors by a vast amount. In this paper, we address the problem of \"tunnel planning\", that is, find a good choice of Blocks to be tunneled. We show that, if Blocks are allowed to overlap each other, the corresponding Block cover and maximum coverage problem are NP-hard, while the Block cover problem is in P if no overlappings are allowed. Furthermore, we present a simple heuristic which outperforms existing solutions for Block choice in the overlapping case both in compression rate and resource requirements.","PeriodicalId":167723,"journal":{"name":"2019 Data Compression Conference (DCC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Data Compression Conference (DCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2019.00022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The Burrows-Wheeler transform is a well known and useful text transformation used for both data compression and text indexing. Recently, a new technique called "tunneling" was presented, improving compression rates of BWT compressors by a vast amount. In this paper, we address the problem of "tunnel planning", that is, find a good choice of Blocks to be tunneled. We show that, if Blocks are allowed to overlap each other, the corresponding Block cover and maximum coverage problem are NP-hard, while the Block cover problem is in P if no overlappings are allowed. Furthermore, we present a simple heuristic which outperforms existing solutions for Block choice in the overlapping case both in compression rate and resource requirements.