In online advertising, the Internet users may be exposed to a sequence of different ad campaigns, i.e., display ads, search, or referrals from multiple channels, before led up to any final sales conversion and transaction. For both campaigners and publishers, it is fundamentally critical to estimate the contribution from ad campaign touch-points during the customer journey (conversion funnel) and assign the right credit to the right ad exposure accordingly. However, the existing research on the multi-touch attribution problem lacks a principled way of utilizing the users' pre-conversion actions (i.e., clicks), and quite often fails to model the sequential patterns among the touch points from a user's behavior data. To make it worse, the current industry practice is merely employing a set of arbitrary rules as the attribution model, e.g., the popular last-touch model assigns 100% credit to the final touch-point regardless of actual attributions. In this paper, we propose a Dual-attention Recurrent Neural Network (DARNN) for the multi-touch attribution problem. It learns the attribution values through an attention mechanism directly from the conversion estimation objective. To achieve this, we utilize sequence-to-sequence prediction for user clicks, and combine both post-view and post-click attribution patterns together for the final conversion estimation. To quantitatively benchmark attribution models, we also propose a novel yet practical attribution evaluation scheme through the proxy of budget allocation (under the estimated attributions) over ad channels. The experimental results on two real datasets demonstrate the significant performance gains of our attribution model against the state of the art.

Once the conceptual overview, in terms of a somewhat informal class diagram, has been designed in the course of engineering an ontology, the process of adding many of the appropriate logical axioms is mostly a routine task. We provide a Protege plugin which supports this task, together with a visual user interface, based on established methods for ontology design pattern modeling.

WestJet Airlines Ltd. has launched an artificial intelligence (AI) powered chatbot, the first of its kind for a Canadian airline. The low-budget airline made the announcement Monday, calling the chatbot a quicker and easier way for its customers to plan and navigate their travel. It's available through Facebook Messenger and according to the release can help travellers with finding travel destinations and can even offer "discovery inspiration" for trips. It also offers day-of travel information. The chatbot, named Juliet is available in English and French and "uses reinforcement learning allowing the chatbot to learn the way humans do, with a combination of instructions, examples, and experience, leading to better responses over time," states the release.

Scientists find that the whiskers of harbor seals help them distinguish predator from prey -- even from a distance. Scientists find that the whiskers of harbor seals help them distinguish predator from prey -- even from a distance. Using lessons learned from harbor seals and artificial intelligence, engineers in California may be on to a new way to track enemy submarines. The idea started with research published in 2001 on the seals. Scientists at the University of Bonn in Germany showed that blindfolded seals could still track a robotic fish. The researchers concluded that the seals did this by detecting the strength and direction of the whirling vortex the robot created as it swam through the water.

Russia's Yandex has taken its self-driving efforts one step further, launching an autonomous ride-hailing service in the university city of Innopolis, Russia. The company claims it's the first such service to launch in Europe. For now, there will be two self-driving vehicles in operation and they'll provide rides to specific locations, such as the university, the stadium and residential blocks, for free. A safety engineer will ride in the passenger seat and around 100 people have agreed to test the service. Yandex unveiled a prototype of its self-driving Prius last year.

The huge fire that gutted a historic Building in Belfast city centre has been filmed from the air.

A California firm has revealed a radical new AI'pilot assistance' system it hopes could change they way we travel. SkyRyse says its first craft will begin operations in Tracy, California, in January where it will provide support to the city's emergency response units, including law enforcement, search and rescue missions, and firefighters. The system will eventually allow helicopters and other vehicles to fly themselves, and its founder hopes to take on Uber and others developing'flying taxi' services. SkyRyse says its first craft will begin operations in Tracy, California, in January providing support to emergency response units. It will eventually allow helicopters and other vehicles to fly themselves.

Vespa's first electric scooter will go on sale in Europe in October and in the US at the start of 2019. The silent, battery-powered scooter is an electric version of the much-loved retro Vespa which was first released back in 1946. The re-imagined all-electric scooter, known as the Vespa Elettrica, has a maximum range of 62 miles (100km) and takes around four hours to charge the battery. Manufacturer Piaggio Group has remained tight-lipped about the price of its new scooter, as well as its top speed. It has previously revealed the Vespa Elettrica will be limited to 19pmh (30km/h) when set in Eco driving mode.

The Russian Ministry of Defence has been keen to promote a range of new super weapons currently believed to be in development. President Putin unveiled a catalogue of doomsday weaponry as part of his annual'State of the Nation' speech in March 2018. However, questions remain about the true nature of their capabilities, how far into development the weapons truly are, and when they will be combat-ready. The RS-28 Sarmat is intended to replace the Soviet-designed SS-18 Voyevoda, the world's heaviest ICBM (Intercontinental Ballistic Missile). It is known as'Satan' in the West and carries 10 nuclear warheads.

Machine learning gets a lot of buzz these days, usually in connection with big data and artificial intelligence (AI). But what exactly is it? Broadly speaking, machine learners are computer algorithms designed for pattern recognition, curve fitting, classification and clustering. The word learning in the term stems from the ability to learn from data. Machine learning is also widely used in data mining and predictive analytics, which some commentators loosely call big data.