Decision intelligence is a framework that supports data and analytics architects model, align, develop, implement and track decision-making models and processes. Decision intelligence is thought to have a huge impact on business results and performance, with Gartner forecasting that over 33% of organizations will have analysts that practice business intelligence by 2023. Decision intelligence connects business problems and applies data science to find appropriate solutions. For this to be achieved, stakeholder behaviors need to be analyzed and incorporated into the decision-making process. Data intelligence is best described as an amalgamation of data science, business intelligence, decision modeling, and overall management.

Sabre Corporation (NASDAQ: SABR), the leading software and technology company that powers the global travel industry, today announced that Sabre and Google are developing an Artificial Intelligence (AI)-driven technology platform that is an industry first in travel. The technology, known as Sabre Travel AI, is infused with Google's state-of-the-art AI technology and advanced machine-learning capabilities that will help customers to deliver highly relevant and personalized content more quickly, deliver personalized content that better meets the demands of today's traveler, and create expanded revenue and margin growth opportunities. The Company is integrating Sabre Travel AI into certain products in its existing portfolio, with plans to bring those to market in early 2021. "Sabre Travel AI is a game-changer. We are proud to be working with Google to build technologies that will seek to re-define the way travel companies do business, and turn the insights derived from analyses into repeatable, scalable operations. The development of Sabre Travel AI marks a milestone in our technology transformation and a significant step toward achieving our 2025 vision of personalized retailing," said Sundar Narasimhan, president of Sabre Labs.

Artificial intelligence (AI) is no longer a futuristic concept found in science fiction films – it is today's technology. The power and capabilities it offers are growing, creating a future filled with possibility. The potential of AI was showcased at a Microsoft event in London recently. Journalists, scientists and researchers heard from Microsoft spokespeople such as Harry Shum, Executive Vice-President of Microsoft AI and Research Group, and Chris Bishop, Laboratory Director at Microsoft Research Cambridge. Among the announcements, including Microsoft's AI for Earth initiative, a number of companies spoke about how they are using the power of AI to drive innovation.

We introduce a semi-supervised discrete choice model to calibrate discrete choice models when relatively few requests have both choice sets and stated preferences but the majority only have the choice sets. Two classic semi-supervised learning algorithms, the expectation maximization algorithm and the cluster-and-label algorithm, have been adapted to our choice modeling problem setting. We also develop two new algorithms based on the cluster-and-label algorithm. The new algorithms use the Bayesian Information Criterion to evaluate a clustering setting to automatically adjust the number of clusters. Two computational studies including a hotel booking case and a large-scale airline itinerary shopping case are presented to evaluate the prediction accuracy and computational effort of the proposed algorithms. Algorithmic recommendations are rendered under various scenarios.