Identifying and monitoring business and technological trends are crucial for innovation and competitiveness of businesses. Exponential growth of data across the world is invaluable for identifying emerging and evolving trends. On the other hand, the vast amount of data leads to information overload and can no longer be adequately processed without the use of automated methods of extraction, processing, and generation of knowledge. There is a growing need for information systems that would monitor and analyse data from heterogeneous and unstructured sources in order to enable timely and evidence-based decision-making. Recent advancements in computing and big data provide enormous opportunities for gathering evidence on future developments and emerging opportunities. The present study demonstrates the use of text-mining and semantic analysis of large amount of documents for investigating in business trends in mobile commerce (m-commerce). Particularly with the on-going COVID-19 pandemic and resultant social isolation, m-commerce has become a large technology and business domain with ever growing market potentials. Thus, our study begins with a review of global challenges, opportunities and trends in the development of m-commerce in the world. Next, the study identifies critical technologies and instruments for the full utilization of the potentials in the sector by using the intelligent big data analytics system based on in-depth natural language processing utilizing text-mining, machine learning, science bibliometry and technology analysis. The results generated by the system can be used to produce a comprehensive and objective web of interconnected technologies, trends, drivers and barriers to give an overview of the whole landscape of m-commerce in one business intelligence (BI) data mart diagram.

中文翻译：

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大数据增强商业趋势识别：移动商务案例

识别和监控业务和技术趋势对于企业的创新和竞争力至关重要。全球数据的指数增长对于识别新兴和不断发展的趋势非常宝贵。另一方面，海量数据导致信息过载，如果不使用自动提取、处理和生成知识的方法，就无法充分处理。越来越需要能够监控和分析来自异构和非结构化来源的数据的信息系统，以实现及时和基于证据的决策。计算和大数据的最新进展为收集有关未来发展和新兴机会的证据提供了巨大的机会。本研究展示了使用文本挖掘和大量文档的语义分析来调查移动商务 (m-commerce) 中的商业趋势。特别是随着持续的 COVID-19 大流行和由此产生的社会隔离，移动商务已成为一个具有不断增长的市场潜力的大型技术和商业领域。因此，我们的研究首先回顾了全球移动商务发展中的全球挑战、机遇和趋势。接下来，该研究通过使用基于深度自然语言处理的智能大数据分析系统，利用文本挖掘、机器学习、科学文献计量学和技术分析，确定了充分利用该行业潜力的关键技术和工具。