利用大数据工具提升旅游体验

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI:10.1109/HPCSim.2015.7237089

Nunzio Cassavia, Pietro Dicosta, E. Masciari, D. Saccá

{"title":"利用大数据工具提升旅游体验","authors":"Nunzio Cassavia, Pietro Dicosta, E. Masciari, D. Saccá","doi":"10.1109/HPCSim.2015.7237089","DOIUrl":null,"url":null,"abstract":"Due to the emerging Big Data applications traditional data management techniques result inadequate in many real life scenarios. In particular, OLAP techniques require substantial changes in order to offer useful analysis due to huge amount of data to be analyzed and their velocity and variety. In this paper, we describe an approach for dynamic Big Data searching that based on data collected by a suitable storage system, enrich data in order to guide users through data exploration in a efficient and effective way.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Improving tourist experience by Big Data tools\",\"authors\":\"Nunzio Cassavia, Pietro Dicosta, E. Masciari, D. Saccá\",\"doi\":\"10.1109/HPCSim.2015.7237089\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the emerging Big Data applications traditional data management techniques result inadequate in many real life scenarios. In particular, OLAP techniques require substantial changes in order to offer useful analysis due to huge amount of data to be analyzed and their velocity and variety. In this paper, we describe an approach for dynamic Big Data searching that based on data collected by a suitable storage system, enrich data in order to guide users through data exploration in a efficient and effective way.\",\"PeriodicalId\":134009,\"journal\":{\"name\":\"2015 International Conference on High Performance Computing & Simulation (HPCS)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on High Performance Computing & Simulation (HPCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSim.2015.7237089\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on High Performance Computing & Simulation (HPCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSim.2015.7237089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 5

摘要

由于大数据应用的兴起，传统的数据管理技术在许多现实生活场景中已经出现了不足。特别是，OLAP技术需要进行大量的更改，以便提供有用的分析，因为要分析的数据量非常大，而且数据的速度和种类都非常多。本文描述了一种动态大数据搜索方法，该方法基于合适的存储系统收集的数据，丰富数据，以高效有效的方式指导用户进行数据探索。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Improving tourist experience by Big Data tools

Due to the emerging Big Data applications traditional data management techniques result inadequate in many real life scenarios. In particular, OLAP techniques require substantial changes in order to offer useful analysis due to huge amount of data to be analyzed and their velocity and variety. In this paper, we describe an approach for dynamic Big Data searching that based on data collected by a suitable storage system, enrich data in order to guide users through data exploration in a efficient and effective way.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2015 International Conference on High Performance Computing & Simulation (HPCS)

自引率

0.00%

发文量