Hackers have stolen personal information about 1.5 million people in a major cyber attack on the Singapore government's health database. More than a quarter of the city state's population was affected by the "deliberate, targeted and well-planned" attack, in which data on patients who visited clinics between May 2015 and 4 July this year was illegally accessed and copied. "It was not the work of casual hackers or criminal gangs," the government said, adding those responsible had been looking to obtain personal details about the prime minister and the medicines he had been proscribed. "The attackers specifically and repeatedly targeted Prime Minister Lee Hsien Loon's personal particulars and information on his outpatient dispensed medicines," said a joint statement by the Health Ministry and the Ministry of Communications and Information. In a statement on his Facebook page, Mr Lee said: "I don't know what the attackers were hoping to find.
Existing computational methods for the analysis of corpora of text in natural language are still far from approaching a human level of understanding. We attempt to advance the state of the art by introducing a model and algorithmic framework to transform text into recursively structured data. We apply this to the analysis of news titles extracted from a social news aggregation website. We show that a recursive ordered hypergraph is a sufficiently generic structure to represent significant number of fundamental natural language constructs, with advantages over conventional approaches such as semantic graphs. We present a pipeline of transformations from the output of conventional NLP algorithms to such hypergraphs, which we denote as semantic hypergraphs. The features of these transformations include the creation of new concepts from existing ones, the organisation of statements into regular structures of predicates followed by an arbitrary number of entities and the ability to represent statements about other statements. We demonstrate knowledge inference from the hypergraph, identifying claims and expressions of conflicts, along with their participating actors and topics. We show how this enables the actor-centric summarization of conflicts, comparison of topics of claims between actors and networks of conflicts between actors in the context of a given topic. On the whole, we propose a hypergraphic knowledge representation model that can be used to provide effective overviews of a large corpus of text in natural language.
Politicians on two continents would love to know where Mark Zuckerberg is. The Facebook CEO opened this year with a public mea culpa after the social media platform he nurtured into global dominance became entangled in congressional enquiries into Russian election meddling, with mounting evidence that Russian surrogates had used the platform to distort and divide. Mr Zuckerberg had already walked back dismissing the notion that Facebook could be a vessel for political chicanery as "crazy", and at the outset of 2018 he pledged to do better. "Facebook has a lot of work to do – whether it's protecting out community from abuse and hate, defending against interference by nation states, or making sure that time spent on Facebook is time well spent," Mr Zuckerberg wrote in – what else – a Facebook post. "My personal challenge for 2018 is to focus on fixing these important issues."
Republicans blasted Google after the search engine briefly identified "Nazism" as one of the tenets of the California Republican party. People searching for more information on the party were, for a time, greeted by a squib summarising information that included the word "Nazism" under an "ideology" section. The characterisation quickly drew a backlash from conservatives. Rep Kevin McCarthy of Bakersfield, California's highest-ranking Republican in Congress, tweeted that the term's inclusion was a "disgrace", adding a "#StoptheBias" hashtag. "Google owes conservatives answers and assurances that they are putting an end to this", Republican National Committee chairwoman Ronna McDaniel said.
Exorbitant legal fees, seemingly endless bureaucracy and an uncertain time investment mean the decision to pursue legal action against a company or an individual is often fraught with hesitation. But the founder of a legal-services app says his product now allows users to sue someone with their smartphones and claim awards from class-action lawsuits the same way they would select a match on Tinder - with a quick "swipe right to sue." Since those new services launched on Wednesday, the app, known as DoNotPay, has been downloaded more than 10,000 times, according to its founder, Joshua Browder, a 21-year-old senior at Stanford University who has been labelled the "Robin Hood of the internet." As an 18-year-old, Mr Browder created a bot that helped people fight parking tickets in New York, London and Seattle, and he later created another bot to help people sue Equifax after a data breach left 143 million American consumers vulnerable to identity theft last year. Mr Browder is the son of businessman Bill Browder, a well-known critic of Russian President Vladimir Putin. He said the idea for his latest project - which works in all 50 states - came about after numerous people used DoNotPay to recoup as much as $11,000 (£8,500) from Equifax, even after the credit reporting agency appealed.