We study the problem of learning from group comparisons, with applications in predicting outcomes of sports and online games. Most of the previous works in this area focus on learning individual effects--they assume each player has an underlying score, and the "ability" of the team is modeled by the sum of team

We study the problem of learning from group comparisons, with applications in predicting outcomes of sports and online games. Most of the previous works in this area focus on learning individual effects--they assume each player has an underlying score, and the "ability" of the team is modeled by the sum of team

Due to the convenience of mobile devices, the online games have become an important part for user entertainments in reality, creating a demand for friend recommendation in online games. However, none of existing approaches can effectively incorporate the multi-modal user features (e.g., images and texts) with the structural information in the friendship graph, due to the following limitations: (1) some of them ignore the high-order structural proximity between users, (2) some fail to learn the pairwise relevance between users at modality-specific level, and (3) some cannot capture both the local and global user preferences on different modalities. By addressing these issues, in this paper, we propose an end-to-end model FROG that better models the user preferences on potential friends. Comprehensive experiments on both offline evaluation and online deployment at Tencent have demonstrated the superiority of FROG over existing approaches.

A unique online game of political skill is engaging players and users not just from across America but from all over the world -- who are learning about the American political system, including the Electoral College, especially as the 2024 presidential election season heats up. Mark J. Penn, chair and CEO of Stagwell Inc., is the creator of a virtual political game of strategy called TwoSeventy. "This is more or less the only serious political online game right now," Penn told Fox News Digital in an interview. "There are online games in which you can catch sharks, kill Mafiosi, shoot people -- but it's pretty rare for you to be able to play a sophisticated political game where you take on the characters in the campaigns and aim to become president," he said. "It's pretty rare for you to be able to play a sophisticated political game where you take on the characters in the campaigns and aim to become president," said Mark Penn, creator of the online game called TwoSeventy.

Chinese authorities have said they may revise newly drafted online gaming rules shortly after the planned restrictions caused major tech companies to lose billions of dollars. State broadcaster CCTV reported on Saturday that the authorities have heard the "concerns and opinions raised by all parties", adding that "the State Press and Publication Administration will study them carefully and further revise and improve them", referring to the media regulator. The authorities released a draft on Friday with a wide range of rules and regulations aimed at curbing online spending and rewards in video games. Its impact was immediate, dealing a massive blow to the world's biggest games market. Investors went into a tailspin, leading to as much as $80bn in market value being wiped off from China's two biggest companies, industry leader Tencent Holdings and Netease.

Developers are taking another shot at a One Punch Man game, but this one is very different than the last major attempt. Anime service Crunchyroll has announced One Punch Man: World, an online multiplayer action title headed to Android, iOS and PC. The free-to-play game has you and friends joining the Hero Association to fight a growing wave of villains through missions and raids. You can unlock and play as heroes from the TV show's first season, including Saitama's faithful sidekick Genos, Mumen Rider and Puri-Puri Prisoner. You can relive key moments from the show, too.

Friend recall is an important way to improve Daily Active Users (DAU) in online games. The problem is to generate a proper lost friend ranking list essentially. Traditional friend recall methods focus on rules like friend intimacy or training a classifier for predicting lost players' return probability, but ignore feature information of (active) players and historical friend recall events. In this work, we treat friend recall as a link prediction problem and explore several link prediction methods which can use features of both active and lost players, as well as historical events. Furthermore, we propose a novel Edge Transformer model and pre-train the model via masked auto-encoders. Our method achieves state-of-the-art results in the offline experiments and online A/B Tests of three Tencent games.

Creating a game with a large, highly engaged online player base and an active community is, for many companies, right at the top of their wishlist. When they're really well managed, these games are a license to print money, to the extent that a single game can become a primary commercial driver of a pretty large company. Games like Fortnite, World of Warcraft, Call of Duty, Grand Theft Auto V, and Final Fantasy XIV, to name but a few, have become central to the ongoing success of the publishers who created and operate them. Their importance rests on the fact that while many popular franchises can rely on a huge launch for each new instalment, these games never actually stop being played and making money. It's no wonder that executives around the industry get dollar signs in their eyes when anyone starts talking about service-based games with high engagement. There are, of course, downsides.

Smart Data AI technology allows online casino games to collect vast amounts of data, allowing them to provide personalized marketing and exclusive promotions to players. Based on this information, online casinos can offer the following to specific players: – Customized advertisements and offers. AI, for example, can swiftly spot patterns and make valuable predictions. Casino games are using artificial intelligence to identify patterns and work based on people's preferences and dislikes. High-level data analysis allows many operators to understand their players' gambling behavior. Spotting Problem Gamblers Typically, gaming authorities do not tolerate gaming addiction since it harms players and the gambling industry.

Ever since he beat the greatest chess player who ever lived, Hans Niemann has been called a cheat. The 19-year-old's surprising victory over Magnus Carlsen in St. Louis on September 4 led to accusations that he'd been taking cues from a chess-playing AI, or chess "engine." Niemann later admitted to having done just that on two occasions--both times when he was even younger, and while he was playing chess online. But he'd beaten Carlsen fairly, he insisted. For weeks now, chess experts have been trying to assess that claim, posting what they've found on social media.