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Investigating spatial and temporal variations of soil moisture content in an arid mining area using an improved thermal inertia model 被引量:5
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作者 WANG Yuchen BIAN Zhengfu +1 位作者 LEI Shaogang ZHANG Yu 《Journal of Arid Land》 SCIE CSCD 2017年第5期712-726,共15页
Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content(SMC). I... Mining operations can usually lead to environmental deteriorations. Underground mining activities could cause an extensive decrease in groundwater level and thus a dramatic variation in soil moisture content(SMC). In this study, the spatial and temporal variations of SMC from 2001 to 2015 at two spatial scales(i.e., the Shendong coal mining area and the Daliuta Coal Mine) were analyzed using an improved thermal inertia model with a long-term series of Landsat TM/OLI(TM=Thematic Mapper and OLI=Operational Land Imager) data. Our results show that at large spatial scale(the Shendong coal mining area), underground mining activities had insignificant negative impacts on SMC and that at small spatial scale(the Daliuta Coal Mine), underground mining activities had significant negative impacts on SMC. Trend analysis of SMC demonstrated that areas with decreasing trend of SMC were mainly distributed in the mined area, indicating that underground mining is a primary cause for the drying trend in the mining region in this arid environment. 展开更多
关键词 mining disturbance spatial-temporal variation soil moisture content thermal inertia Shendong coal mining area
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A Novel Metadata Based Multi-Label Document Classification Technique
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作者 Naseer Ahmed Sajid Munir Ahmad +13 位作者 Atta-ur Rahman Gohar Zaman Mohammed Salih Ahmed Nehad Ibrahim Mohammed Imran BAhmed Gomathi Krishnasamy Reem Alzaher Mariam Alkharraa Dania AlKhulaifi Maryam AlQahtani Asiya A.Salam Linah Saraireh Mohammed Gollapalli Rashad Ahmed 《Computer Systems Science & Engineering》 SCIE EI 2023年第8期2195-2214,共20页
From the beginning,the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies,its growth rate is overwhelming.On a rough estimate,more than thirty thousand res... From the beginning,the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies,its growth rate is overwhelming.On a rough estimate,more than thirty thousand research journals have been issuing around four million papers annually on average.Search engines,indexing services,and digital libraries have been searching for such publications over the web.Nevertheless,getting the most relevant articles against the user requests is yet a fantasy.It is mainly because the articles are not appropriately indexed based on the hierarchies of granular subject classification.To overcome this issue,researchers are striving to investigate new techniques for the classification of the research articles especially,when the complete article text is not available(a case of nonopen access articles).The proposed study aims to investigate the multilabel classification over the available metadata in the best possible way and to assess,“to what extent metadata-based features can perform in contrast to content-based approaches.”In this regard,novel techniques for investigating multilabel classification have been proposed,developed,and evaluated on metadata such as the Title and Keywords of the articles.The proposed technique has been assessed for two diverse datasets,namely,from the Journal of universal computer science(J.UCS)and the benchmark dataset comprises of the articles published by the Association for computing machinery(ACM).The proposed technique yields encouraging results in contrast to the state-ofthe-art techniques in the literature. 展开更多
关键词 Multilabel classification INDEXING METADATA content/data mining
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基于网络文本分析的拉萨市旅游体验研究 被引量:2
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作者 李国栋 《安徽职业技术学院学报》 2020年第2期1-4,9,共5页
文章通过收集、整理和加工游客对拉萨市旅游评价和感受的网络文本数据,运用ROST Content Mining软件对样本数据分析并提取游客对拉萨市旅游直观感受的高频词,从而了解游客对拉萨市旅游体验的内容和主题,以探究游客对拉萨市旅游体验的感... 文章通过收集、整理和加工游客对拉萨市旅游评价和感受的网络文本数据,运用ROST Content Mining软件对样本数据分析并提取游客对拉萨市旅游直观感受的高频词,从而了解游客对拉萨市旅游体验的内容和主题,以探究游客对拉萨市旅游体验的感知、印象,为拉萨市旅游业的发展和旅游体验的完善及提升提供一定依据。 展开更多
关键词 拉萨市 旅游体验 网络文本分析法 ROST content mining
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基于网络文本分析的游客对永泰天门山景区旅游形象感知研究 被引量:2
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作者 林梁栋 王文婷 +2 位作者 赖启福 林凌 李虎峰 《河南科技大学学报(社会科学版)》 2021年第3期33-38,共6页
运用网络文本内容分析法,通过ROST Content Mining软件提取永泰县天门山旅游形象的高频特征词,形成语义结构图,从自然环境、景区景点、旅游设施以及文化历史和艺术感知四个角度来研究游客对永泰县天门山景区的旅游形象感知。结果表明:... 运用网络文本内容分析法,通过ROST Content Mining软件提取永泰县天门山旅游形象的高频特征词,形成语义结构图,从自然环境、景区景点、旅游设施以及文化历史和艺术感知四个角度来研究游客对永泰县天门山景区的旅游形象感知。结果表明:游客对天门山的旅游形象偏向于积极感知,符合其“仙境”美称;而消极感知主要来源于自然景观缺乏独特性、旅游设施不完善等方面。提出合理利用景区资源优势,挖掘人文特色,丰富旅游形象;完善设施建设,提高服务质量;建立研究及顾问机构,更深层次的提升景区整体质量水平;开发管理信息系统,实现精准高效控制;构建信息互动机制;选择相契合的景区进行联动发展六条建议。 展开更多
关键词 形象感知 网络文本分析 ROST content mining 永泰天门山景区
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TOTAL CONTENTS Big Data Mining and Analytics, Vol. 1, 2018
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《Big Data Mining and Analytics》 2018年第4期335-336,共2页
关键词 TOTAL contentS Big Data mining and Analytics VOL
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TOTAL CONTENTS Big Data Mining and Analytics, Vol. 2, 2019
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《Big Data Mining and Analytics》 2019年第4期349-350,共2页
关键词 TOTAL contentS Big Data mining and Analytics VOL
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