Customers in the UK will soon find out. Recent reports suggest that three of the country's largest supermarket chains are rolling out surge-pricing in select stores. This means that prices will rise and fall over the course of the day in response to demand. Buying lunch at lunchtime will be like ordering an Uber at rush hour. This may sound pretty drastic, but far more radical changes are on the horizon.
Every industry can benefit from Big Data, IoT and AI, and that includes brewers. Dutch brewer Heineken has been a worldwide brewing leader for the last 150 years, but today, as the No. 1 brewer in Europe and No. 2 in the world they are ramping up their results thanks to the use of big data and AI. As the company sets out to better compete in the formidable U.S. beer market they plan to leverage the vast amounts of data they collect. Currently they sell more than 8.5 million barrels of its various beer brands here in the U.S., but they hope to increase those numbers with data-driven improvements and AI augmentation to its operations, marketing, advertising and customer experience.
It is often desirable to extract structured information from raw web pages for better information browsing, query answering, and pattern mining. many such Information Extraction (IE) technologies are costly and applying them at the web-scale is impractical. In this paper, we propose a novel prioritization approach where candidate pages from the corpus are ordered according to their expected contribution to the extraction results and those with higher estimated potential are extracted earlier. Systems employing this approach can stop the extraction process at any time when the resource gets scarce (i.e., not all pages in the corpus can be processed), without worrying about wasting extraction effort on unimportant pages. More specifically, we define a novel notion to measure the value of extraction results and design various mechanisms for estimating a candidate page’s contribution to this value. We further design and build the Extraction Prioritization (EP) system with efficient scoring and scheduling algorithms, and experimentally demonstrate that EP significantly outperforms the naive approach and is more flexible than the classifier approach.
There's a funny internet meme doing the rounds of a little boy asking Mark Zuckerberg if it's true what his dad says that Facebook is spying on people, to which Zuckerberg simply responds'he's not your dad'. But while the Cambridge Analytica saga may have done some serious PR damage in the short term, big data's here to stay. Advertising companies, insurers and supermarkets have been using big data for quite some time now because it allows them to better tailor their products to their users. At Valé, we predict a huge shift over the next ten years in hospitality design. It's a shift where predictive behavioural analysis will gradually replace the industry's traditional reliance on intuition and guesswork – hopefully putting an end to wasteful design once and for all.