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Record Nr. |
UNINA9910349309303321 |
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Titolo |
Web and Big Data : Third International Joint Conference, APWeb-WAIM 2019, Chengdu, China, August 1–3, 2019, Proceedings, Part I / / edited by Jie Shao, Man Lung Yiu, Masashi Toyoda, Dongxiang Zhang, Wei Wang, Bin Cui |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (XX, 433 p. 133 illus., 102 illus. in color.) |
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Collana |
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Information Systems and Applications, incl. Internet/Web, and HCI ; ; 11641 |
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Disciplina |
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Soggetti |
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Information storage and retrieval |
Artificial intelligence |
Algorithms |
Computer science—Mathematics |
Application software |
Data structures (Computer science) |
Information Storage and Retrieval |
Artificial Intelligence |
Algorithm Analysis and Problem Complexity |
Discrete Mathematics in Computer Science |
Computer Appl. in Social and Behavioral Sciences |
Data Structures |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Big Data Analytics -- Data and Information Quality -- Data Mining and Application -- Graph Data and Social Networks -- Information Extraction and Retrieval -- Knowledge Graph -- Machine Learning -- Recommender Systems -- Storage, Indexing and Physical Database Design -- Spatial, Temporal and Multimedia Databases -- Text Analysis and Mining. . |
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Sommario/riassunto |
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This two-volume set, LNCS 11641 and 11642, constitutes the |
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thoroughly refereed proceedings of the Third International Joint Conference, APWeb-WAIM 2019, held in Chengdu, China, in August 2019. The 42 full papers presented together with 17 short papers, and 6 demonstration papers were carefully reviewed and selected from 180 submissions. The papers are organized around the following topics: Big Data Analytics; Data and Information Quality; Data Mining and Application; Graph Data and Social Networks; Information Extraction and Retrieval; Knowledge Graph; Machine Learning; Recommender Systems; Storage, Indexing and Physical Database Design; Spatial, Temporal and Multimedia Databases; Text Analysis and Mining; and Demo. |
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