Game of Thrones characters and many other fantasy novels pose an issue for technology designed to decipher languages and the written word. Quirky names, such as Daenerys and Grey Worm, don't look or resemble most names from the real world and are often not picked up by technology as they don't behave in a normal manner. The algorithms are developed and trained to detect names by studying newspaper articles. A vastly different writing style is found in non-fiction novels and makes the detection of fictional names almost impossible. Names are contextualised in stories and this also adds another layer to the thorny issue.

According to sophisticated machine-learning calculations, the Queen of Dragons will soon meet her demise. In early July, a computer scientist at Central European University's Center for Network Science, Milan Janosov, predicted the fates of the Game of Thrones characters that have yet to be impaled, poisoned, or have their brains bludgeoned. He quantified their social significance on the show, and then entered these numbers into a machine-learning algorithm. To create his algorithm, Janosov first built a network of the realm's social system based on how often characters interacted with each other. He pulled this data from the show's subtitles, which provided nearly 600 scenes worth of information about how often characters appeared in the same scene.

"There is one thing we say to death. Master sword fighter Syrio Forel's wisecrack in the first season of popular TV series, "Game of Thrones," made Miltos Yerolemou's short role -- as Arya Stark's sword instructor -- in the show memorable. Forel died in the eighth episode but her student, who got to hear the wisecrack during one of the training sessions, has turned out to become one of the strongest characters in the television adaptation of epic fantasy novel, "A Song of Ice and Fire," authored by show producer George R R Martin. Its seventh season premiered last week. Like Arya, most survivors on the wildly unpredictable show have defied death more than once. With a devoted fan base of millions across the world, "Game of Thrones" has its loyalists hooked for the penultimate season as the contenders to the Iron Throne get further embroiled in the power struggle. While the Harvard University may soon be getting a humanities course based on the saga, it has also inspired a research predicting the death of the lead characters using machine learning methods. In the research, author Milán Janosov used the show's subtitles, collected in dialogue format on a fan website, as the data source. "We have a set of 94 characters interesting enough to care about.