This edited book provides a platform to bring together researchers, academia and industry collaborators to exchange their knowledge and work to develop better understanding about the scope of blockchain technology in business management applications of different sectors such as retail sector, supply chain and logistics, healthcare sector, manufacturing sector, judiciary, finance and government sector in terms of data quality and timeliness. The book presents original unpublished research papers on blockchain technology and business management on novel architectures, prototypes and case studies.

This edited book provides a platform to bring together researchers, academia and industry collaborators to exchange their knowledge and work to develop better understanding about the scope of blockchain technology in business management applications of different sectors such as retail sector, supply chain and logistics, healthcare sector, manufacturing sector, judiciary, finance and government sector in terms of data quality and timeliness. The book presents original unpublished research papers on blockchain technology and business management on novel architectures, prototypes and case studies.

This book constitutes the refereed joint proceedings of four international workshops held in conjunction with the 8th Asia-Pacific Web Conference, APWeb 2006, in Harbin, China in January 2006. The 88 revised full papers and 58 revised short papers presented are very specific and contribute to enlarging the spectrum of the more general topics treated in the APWeb 2006 main conference.

The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.

The two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.

This two-volume set of LNAI 12274 and LNAI 12275 constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.*The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning. *The conference was held virtually due to the COVID-19 pandemic.

This two-volume set of LNAI 12274 and LNAI 12275 constitutes the refereed proceedings of the 13th International Conference on Knowledge Science, Engineering and Management, KSEM 2020, held in Hangzhou, China, in August 2020.*The 58 revised full papers and 27 short papers were carefully reviewed and selected from 291 submissions. The papers of the first volume are organized in the following topical sections: knowledge graph; knowledge representation; knowledge management for education; knowledge-based systems; and data processing and mining. The papers of the second volume are organized in the following topical sections: machine learning; recommendation algorithms and systems; social knowledge analysis and management; text mining and document analysis; and deep learning. *The conference was held virtually due to the COVID-19 pandemic.

Financing Entrepreneurship and Innovation in China provides an overview of the current state-of-affairs in the financing of private innovations in China. While country-level innovation can take many forms, the focus is on the funding of business start-ups and entrepreneurial ventures. The monograph has four specific objectives: (1) to present an economic framework for evaluating the central challenges associated with the financing of entrepreneurial ventures in China, (2) to evaluate the relative size and importance of the channels through which private initiatives for innovation in China are currently being funded, (3) to survey the academic evidence on potential financing constraints currently facing private initiatives in innovation, and (4) to discuss public policy implications that may arise from these findings, as well as to outline the type of future research that may best inform Chinese policy makers. After the introduction, Section 2 begins with a review of the central economic themes in entrepreneurial finance. Section 3 reviews the channels through which external funding now reach entrepreneurs in China. Section 4 further explores the problems engendered by China's IPO regulations. Section 5 summarizes the findings, discusses policy implications, and explores potential venues for future research. The authors conclude that China's current IPO regulations represent a serious impediment to two important near-term goals espoused by the Chinese government - to bring more high-technology firms back to mainland stock markets, and to be included at a meaningful weight in international stock indices, particularly the MSCI Emerging Market Index.