Tools and Techniques for Quantum Business

Recommender systems are an Artificial Intelligence technology that has become an essential part of business for many industries and businesses.Recommender Systems (RSs) are software tools and techniques providing suggestions for items to be of use to a user.The system learns from a customer and recommends products that she will find most valuable from among the available products.They serve many types of E-commerce applications, from direct product recommendation for an individual to helping someone find a gift for a third party [10].Recently the world of the web has become more social and more real-time.Facebook and Twitter [16] are perhaps the exemplars of a new generation of social, real-time web services and we believe these types of service provide a fertile ground for recommender systems research.In this research project, the researcher tries to provide a present an analysis of how recommender systems can be used in E-commerce today, companies, SMEs, and other social institutions to improve sales, maintain good customer relationship and loyalty, and saves customers sourcing time.Recommender Systems too can also be used to analyze Big Data, although there are some key challenges associated with Big Data analytics.The impact of data abundance extends well beyond business [15].But the computer tools for gleaning knowledge and insights from the Internet era's vast trove of unstructured data are fast gaining ground.At the forefront are the rapidly advancing techniques of artificial intelligence like natural-language processing, pattern recognition and machine learning.The researcher hopes that these key problems with improved recommender systems in the future: hybrid data, predictable recommendations, scalability, and incorporation of content, such problems could be resolved.If recommender systems are able to surmount these challenges, they have the potential to become an essential component of doing business in Ecommerce

Koen Groenland

Quinn Peterson

B. Collins

DOI: 10.1049/ic:20050578 ISBN: 0-86341-590-3 Location: London, UK Conference date: 7 Dec. 2005 Format: PDF This paper presents a slide presentation of the business impact of quantum cryptography. The pragmatics of quantum cryptography are also included in the presentation. (3 pages) Inspec keywords: business communication; quantum cryptography; telecommunication security; quantum computing Subjects: Cryptography; Quantum computing techniques; Cryptography theory; Data security

S. Varalakshmi, Anupam Sharma, Latifa Saud Al Habsi +1 more

This chapter discusses the means whereby QML can revolutionize and transform online marketing and business practices. QML is a derivative from the principles of quantum computation and machine learning, such that tremendous volumes of data may be processed at unprecedented velocities, hence advanced analytics in terms of customer behavior being made possible, and also that of hyper-personalized marketing campaigns. Some of the key QML techniques discussed in terms of increasing the efficiency of marketing, reducing costs, and improving return on investments include techniques in quantum algorithms for clustering, classification, and optimization. It explores the potential of quantum technology in business intelligence, including real-time customer segmentation, predictive analytics, and dynamic pricing models, and predicts future trends and adoption roadmaps in the digital economy.

Rubyet Islam