The satisfiability problem for SPARQL 1.0 patterns is undecidable in general, since the relational algebra can be emulated using such patterns. The goal of this paper is to delineate the boundary of decidability of satisfiability in terms of the constraints allowed in filter conditions. The classes of constraints considered are bound-constraints, negated bound- constraints, equalities, nonequalities, constant-equalities, and constant-nonequalities. The main result of the paper can be summarized by saying that, as soon as inconsistent filter conditions can be formed, satisfiability is undecidable. The key insight in each case is to find a way to emulate the set difference operation. Undecidability can then be obtained from a known undecidability result for the algebra of binary relations with union, composition, and set difference. When no inconsistent filter conditions can be formed, satisfiability is decidable by syntactic checks on bound variables and on the use of literals. Although the problem is shown to be NP-complete, it is experimentally shown that the checks can be implemented efficiently in practice. The paper also points out that satisfiability for the so-called ‘well-designed’ patterns can be decided by a check on bound variables and a check for inconsistent filter conditions.

Inbenta is a company specialized in Artificial Intelligence and Natural Language Processing which was born in Barcelona and nowadays has presence in 8 different countries (Spain, USA, Chile, Brasil, Mexico, France, The Netherlands and Singapore).

For the past year, Tara Hutchinson has been trying to figure out what will happen to a tall building made from thin steel beams when "the big one" hits. To do that, she has erected a six-story tower that rises like a lime-green finger from atop a shrub-covered hill on the outskirts of San Diego, California. Hundreds of strain gauges and accelerometers fill the building, so sensitive they can detect wind gusts pressing against the walls. Now, Hutchinson just needs an earthquake. In most of the world, this would be a problem.

A team of scientists has developed a model that can predict bat species most likely to transmit Ebola and other filoviruses. Findings highlight new potential hosts and geographic hotspots worthy of surveillance. So reports a new paper in the journal PLoS Neglected Tropical Diseases. Filoviruses have devastating effects on people and primates, as evidenced by the 2014 Ebola outbreak in West Africa. For nearly 40 years, preventing spillover events has been hampered by an inability to pinpoint which wildlife species harbor and spread the viruses.

In one month from now, the second edition of the Data Science Game, an international competition of data science for students, will start (more info here). Students in last year of Masters or PhDs from all around the world will be challenged through an online competion (June 17 to July 10) and a final hackathon (september 10-11). The first 20 teams of the online phase will come to Paris to demonstrate their skills and abilities to solve a data science challenge and meet professional data scientists coming from leading companies in Data Science (Microsoft, CapGemini, Axa Data Innovation Lab, etc.). We think our participants would love to learn from your data challenge experience since you were the former top ranked kaggler. But first of all, can you quickly introduce yourself?

A seemingly nondescript galaxy is actually a behemoth cobbled together out of various cosmic spare parts, Frankenstein-style, a new study suggests. UGC 1382, which lies about 250 million light-years from Earth, had long been regarded as an old, small and ordinary elliptical galaxy. But new observations show that it's actually a spiral, 718,000 light-years wide -- seven times larger than Earth's own Milky Way. "The center of UGC 1382 is actually younger than the spiral disk surrounding it," study co-author Mark Seibert, of the Observatories of the Carnegie Institution for Science in Pasadena, California, said in a statement. This is like finding a tree whose inner growth rings are younger than the outer rings."

Event[0] is a game about a stranded astronaut talking to an artificial intelligence to help them get back to earth. Like Firewatch before it, much of this solitary adventure is centered around conversing with your colleague. Unlike Firewatch, your colleague is a computer recalling 2001's HAL. Also unlike Firewatch, you get to manually type in the questions you'd like to ask. There's no prescribed dialogue trees here, folks.

Even though we are social animals, managing relationships is not an easy task. Everyday interactions with people around us can become tricky as stress, anger, exhaustion, and other emotions start affecting the way we and others react to different situations. The inability to correctly "read" other people and understand how we should treat them causes disagreements and even fights. All these struggles have led to numerous investigations about humans' interactions, resulting in the creation of a term researchers Peter Salavoy and John Mayer coined Emotional Intelligence (EQ or EI). Recently, conversations about the relationship between EI and artificial intelligence have developed.

The new plugin gives businesses a simple way to create and deploy customer support messenger bots; providing their customers with a real-time chat experience that combines a hybrid of AI self-service support and on-demand live agent chat. Integrated with Inbenta's powerful semantic search technology, the Chatbot Creation Platform enables a company to leverage its existing knowledge base to create the chatbot experience. The knowledge base -- or customer FAQs -- are no more than a sequence of answers to common questions; because the content is founded on natural language, the customer exchange becomes a two-way conversation. Inbenta specializes in Natural Language Processing and semantic search to improve the customer experience online through Artificial Intelligence-powered technology that helps businesses increase the efficiency of its customer service, call centers, e-Commerce, FAQs and social media platforms. Support services such as dynamic FAQs, knowledge management and and virtual assistants improve business website searches, customer self-service, and e-Commerce conversions.

Everywhere you look today, there are examples cropping up of how machine learning is revolutionising different industries. In media and entertainment, Spotify and Netflix sort through billions of data points to find patterns in music, films and television that consumers have enjoyed -- and then make suggestions based on their tastes. In retail, Amazon prompts consumers to buy everything from nappies to office chairs based on shoppers' previous purchases. In finance, machine learning is helping investors anticipate market trends and powering innovations underlying everything from self-driving cars to voice-assistant applications. In the payments industry, machine learning is similarly becoming an increasingly important tool to help businesses combat fraud.