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Titlebook: Indigeneity, Development and Sustainability; Perspectives from No Anjan Chakrabarti,Gorky Chakraborty,Anup Shekhar C Book 2024 The Editor(s

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书目名称Indigeneity, Development and Sustainability
副标题Perspectives from No
编辑Anjan Chakrabarti,Gorky Chakraborty,Anup Shekhar C
视频video
概述Accurately depicts the broad canvas and micro-analysis of India‘s Northeast.Explores a diverse range of topics, including material mobilities and contested identities in India‘s Northeast.Presents a n
丛书名称Demographic Transformation and Socio-Economic Development
图书封面Titlebook: Indigeneity, Development and Sustainability; Perspectives from No Anjan Chakrabarti,Gorky Chakraborty,Anup Shekhar C Book 2024 The Editor(s
描述.This volume presents cutting-edge research on India‘s Northeast region relating to borders, material mobilities, contested identities, and economic and political dynamics. It offers a comprehensive understanding of the developmental challenges currently faced by Northeast India, including the complexities of the labor market and the neoliberal economy. The book highlights the lived experiences of individuals in varied geographies and perspectives. It is organized into five sections, each addressing the region‘s old and vexed questions of ‘development‘, and its complicated relationship with indigeneity and sustainability. Contributions from scholars of various disciplines provide an all-inclusive picture of the region, ranging from a macro to a micro level. Interdisciplinary in nature, the book interests a cross-section of academics and graduate students from different disciplines, including sociology, social anthropology, economics, political science, human geography, history, public policy, and development studies..
出版日期Book 2024
关键词Northeast India studies; Historicising Development; Ethnic Communities; Fluidities and Borderlands; Poly
版次1
doihttps://doi.org/10.1007/978-981-97-1436-0
isbn_softcover978-981-97-1438-4
isbn_ebook978-981-97-1436-0Series ISSN 2543-0041 Series E-ISSN 2543-0068
issn_series 2543-0041
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Rakhee Bhattacharya. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrates the capability of the approach in detecting bad mouthing attack in various scenarios.
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Anup Shekhar Chakrabortythin datasets of varied densities and its high computational complexity; hence a number of augmented forms of DBSCAN algorithm are available. We present an incremental density-based clustering technique which is based on the fundamental DBSCAN clustering algorithm to enhance its computational comple
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Anup Shekhar Chakrabortyng sessions are recorded in a transaction database as attributes specifying the features. In order to discover the relations among the features in the transaction databases, algorithms for association rule mining are proposed based on computational intelligence. In the future, these rules could enab
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