Artificial intelligence technologies are currently at the core of many sectors and industries—from cyber security to healthcare—and also have the power to influence the governance of domestic industry, the security and privacy citizens. In particular, the rise of new machine learning methods, such as those used in recommendation systems, provides many opportunities in terms of personalization. Big players like YouTube, Amazon, Netflix, Spotify, and many others are currently using recommendation systems to improve their business. Recommender systems are critical in some industries as they can generate income and provide a way to stand out from competitors. In this chapter, a literature review of recommendation systems is presented, as well as the application of recommendation systems in industry.
TopIntroduction
Artificial Intelligence (AI) can be defined as the study of programmed systems that can simulate human intelligence and activities, such as perceiving, thinking, learning, and acting. Examples of these tasks are visual perception, speech recognition, decision-making, and translation between languages. Artificial intelligence is already part of our everyday lives: self driving cars, navigation systems, chatbots, smart non-player characters. AI has developed as a field of research but also as a technology that expands across a wide range of applications. What differentiates AI from other digital technologies is that AIs are set to learn from their environments in order to take autonomous decisions.
From a business perspective, AI systems have the potential to deliver several advantages that lead to increased productivity. In particular, the most common benefits of AI reside in forecasting, empirical decision-making, operations automation, personalized customer services, enhanced user experiences, process and product optimization, new business models, greater access to services.
Overall venture capital funding for start-ups specializing in AI applications grew by a compound annual growth rate of 85% between 2012 and 2017. Funding tripled between 2016 and 2017, reaching over 11 billion euro (Venture Scanner, 2017). Regardless of the approach pursued, it emerges that countries are engaged in a sort of AI race that aims at achieving AI leadership, and the demand of AI is exponentially growing.
Many companies are currently using Artificial Intelligence to boost their businesses, such as Google (DeepMind’s deep learning technology), Microsoft (Cortana, Azure AI), Disney (Disneyland wristbands), Netflix, and others. Google is one of the pioneers of deep learning since Google Brain project in 2011. Google use deep learning to provide better video recommendation on YouTube, studying viewer’s habits and preferences when they stream content, to help self-driving cars. Virtual assistant Cortana helps you to use windows 10 systems and chatbots in Skype can interact with you and give you some suggestions. Furthermore, Microsoft lets other companies use Microsoft AI Platform to create their own intelligent tools (e.g. Microsoft Azure AI). Disney gives wristbands to every visitor. These can be used as ID, hotel room key, ticket, FastPasses and a payment system. The wristbands collect data obtained from the visitor history and predict guest’s needs to deliver a personalized experience. Netflix uses AI to recommend you films based on things you watch, actors involved, genre, filming location, etc. Other popular examples of AI that’s being used today are: Siri (Apple’s pseudo-intelligent digital personal assistant that uses ML to get smarter and better able to predict and understand our natural language questions and requests), Alexa, Tesla, Cogito, Boxever, Amazon.com. American Express uses AI to spot divergence in client’s financial behaviour patterns, using rule-based systems able to identify transactions that indicate fraudulent activities. In retail, AI can use natural language tools to search on social media for user preferences and come up with a list of recommended items that users are less likely to discover by themselves.