Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Valentina Emilia Balas,Neha Sharma,Amlan Chakrabar Conference proceedings 2

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书目名称Data Management, Analytics and Innovation影响因子(影响力)




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书目名称Data Management, Analytics and Innovation网络公开度学科排名




书目名称Data Management, Analytics and Innovation被引频次




书目名称Data Management, Analytics and Innovation被引频次学科排名




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书目名称Data Management, Analytics and Innovation年度引用学科排名




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nauseate

使人烦燥

armistice

Conference proceedings 2019of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies. It deals with the state-of-the-art topics and provides challenges and solutions for future development. Original, unpublished research work highlightin

摇曳的微光

2194-5357 s and solutions for future development.Serves as a referenceThe volume on .Data Management, Analytics and Innovations. presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and d

思考而得

Zheng Xu,Jinping Li,Jianqin Yin,Yanchun Wuracting explicit temporal expressions and probabilistic in extracting implicit boundaries. We introduce event context as a set of features to learn a CRF model. We achieve F1 score of 0.78 in detecting boundaries. We apply rule-based normalization and ordering of identified temporal expressions.

思考而得

https://doi.org/10.1007/978-981-99-8021-5onverted to a tree for better visualization and easy exploration of data. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on 20 Newsgroup Dataset. Results depict that the presented method is considerably successful in forming topic hierarchy.

Original

Hierarchical Summarization of Text Documents Using Topic Modeling and Formal Concept Analysisonverted to a tree for better visualization and easy exploration of data. To signify the effectiveness of the approach, we have carried out the experiment and evaluation on 20 Newsgroup Dataset. Results depict that the presented method is considerably successful in forming topic hierarchy.

cinder

阐明