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Web Information Systems Engineering - WISE 2023 edited by Feng Zhang, Hua Wang, Mahmoud Barhamgi, Lu Chen, Rui Zhou. [electronic resource] :

Contributor(s): Material type: TextTextPublication details: Singapore Springer Nature Singapore 2023Edition: 1st ed. 2023Description: XX, 956 p. 298 illus., 237 illus. in color. online resourceISBN:
  • 9789819972548
Subject(s): DDC classification:
  • 5.3
Online resources: Summary: This book constitutes the proceedings of the 24th International Conference on Web Information Systems Engineering, WISE 2023, held in Melbourne, Victoria, Australia, in October 2023. The 33 full and 40 short papers were carefully reviewed and selected from 137 submissions. They were organized in topical sections as follows: text and sentiment analysis; question answering and information retrieval; social media and news analysis; security and privacy; web technologies; graph embeddings and link predictions; predictive analysis and machine learning; recommendation systems; natural language processing (NLP) and databases; data analysis and optimization; anomaly and threat detection; streaming data; miscellaneous; explainability and scalability in AI.
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Holdings
Item type Home library Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Available Platform:Springer EB2808
Total holds: 0

This book constitutes the proceedings of the 24th International Conference on Web Information Systems Engineering, WISE 2023, held in Melbourne, Victoria, Australia, in October 2023. The 33 full and 40 short papers were carefully reviewed and selected from 137 submissions. They were organized in topical sections as follows: text and sentiment analysis; question answering and information retrieval; social media and news analysis; security and privacy; web technologies; graph embeddings and link predictions; predictive analysis and machine learning; recommendation systems; natural language processing (NLP) and databases; data analysis and optimization; anomaly and threat detection; streaming data; miscellaneous; explainability and scalability in AI.

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