In a news recommender system, a reader's preferences change over time. Some preferences drift quite abruptly (short-term preferences), while others change over a longer period of time (long-term preferences). Although the existing news recommender systems consider the reader's full history, they often ignore the dynamics in the reader's behavior. Thus, they cannot meet the demand of the news readers for their time-varying preferences. In addition, the state-of-the-art news recommendation models are often focused on providing accurate predictions, which can work well in traditional recommendation scenarios. However, in a news recommender system, diversity is essential, not only to keep news readers engaged, but also to play a key role in a democratic society. In this PhD dissertation, our goal is to build a news recommender system to address these two challenges. Our system should be able to: (i) accommodate the dynamics in reader behavior; and (ii) consider both accuracy and diversity in the design of the recommendation model. Our news recommender system can also work for unprofiled, anonymous and short-term readers, by leveraging the rich side information of the news items and by including the implicit feedback in our model. We evaluate our model with multiple evaluation measures (both accuracy and diversity-oriented metrics) to demonstrate the effectiveness of our methods.

Sony debuted its immersive 360 Reality Audio music format in 2019. But until now, if you wanted to tap into the limited content library, you had to rely on another company's speakers to do so -- like Amazon's Echo Studio. As part of its plans to expand 360 Reality Audio, Sony revealed that two speaker models of its own would go on sale this spring: the SRS-RA3000 and SRS-RA5000. We didn't have to wait long for details. During CES, the company's UK site posted full specs on both speakers.

Organizing smart home gadgets into a single cohesive whole is already a bit of a nightmare. You likely have some kind of smart speaker--a Google Nest or Amazon Echo--and a collection of smart bulbs, thermostats, locks, or cameras that may or may not be made by the same company. Many of them work with each other, but most services assume a single person in the household owns and is setting up everything. This can make it a little difficult to separate all the devices you own when someone moves out, or after a breakup. Who knows what buried setting is going to give someone access to lights or locks they shouldn't be able to control?

Artificial intelligence (AI) is the basis for mimicking human intelligence processes through the creation and application of algorithms built into a dynamic computing environment. Stated simply, AI is trying to make computers think and act like humans. The more humanlike the desired outcome, the more data and processing power required. At least since the first century BCE, humans have been intrigued by the possibility of creating machines that mimic the human brain. In modern times, the term artificial intelligence was coined in 1955 by John McCarthy. In 1956, McCarthy and others organized a conference titled the "Dartmouth Summer Research Project on Artificial Intelligence."

Keeping up with technology at home and at work can be challenging and it may take you out of your comfort zone. However, artificial intelligence (AI) can transform life around your home for the better with its convenient factors and dynamic functionality. Before you put a pause on your home tech upgrades, you'll want to consider what the latest generation of AI solutions can do to improve life at home. Artificial intelligence refers to the engineering of intelligent machines, designing them in such a way to simulate human intelligence. Of course, 'human' is a misnomer here.

Progressive utilization of Artificial Intelligence software in the market for computerization of the procedures, programming, and other purposes has become common. AI-based platforms feature profound machine calculations and learning for robotizing business processes. Automation saves a lot of time and energy of the employees. Here is my personal list of the ten best artificial intelligence software. Automation empowers the organization to perform the working all the more efficiently and profitably.

The hit TV anthology'Black Mirror' has captivated viewers with speculative tales of how emerging technologies like artificial intelligence, machine learning and intelligent automation could go horribly awry. It makes for great television, but do similar futures await learning leaders who are looking to strategically leverage these technologies? We have seen where AI-powered digital technologies are steadily and increasingly becoming part of our daily lives. Amazon's Alexa, Apple's Siri, Google's Assistant and Microsoft's Cortana are accessible in many of our homes and through our digital devices. These and other AI agents are evolving and becoming more capable of completing processes humans are traditionally tasked with.

The $3 billion Online Dating industry has seen a rise of all kinds of apps for all kinds of dating: traditional, long term dating, hook-ups, gay, lesbian, queer, group, "friends of friends", Ivy League, DNA, astrology - you name it! In fact, online dating apps are becoming so popular that over 50% of couples will meet online by 2031, according to eHarmony. Hundreds of millions of users hooked on apps allow dating companies to accumulate incredible amounts of data. This data advances the technology behind dating services enabling not only AI matchmaking but also a more secure and enjoyable online experience. Take a look at our AI In Dating Innovation Landscape which includes 50 rising startups as well as mature companies that leverage AI to make dating more efficient, fun, and safe.

Maybe you rely on Siri or the assistant built into your phone, but you likely have a full-fledged AI assistant in your home, too. Alexa, built into the Amazon Echo, is everywhere. If you have an Echo, there's a good chance Alexa has driven you up the wall a time or two with the follow-up questions. Tap or click here for 5 quick fixes to Amazon Echo annoyances. While you're poking around the settings, don't ignore security.

Visualization recommendation systems simplify exploratory data analysis (EDA) and make understanding data more accessible to users of all skill levels by automatically generating visualizations for users to explore. However, most existing visualization recommendation systems focus on ranking all visualizations into a single list or set of groups based on particular attributes or encodings. This global ranking makes it difficult and time-consuming for users to find the most interesting or relevant insights. To address these limitations, we introduce a novel class of visualization recommendation systems that automatically rank and recommend both groups of related insights as well as the most important insights within each group. Our proposed approach combines results from many different learning-based methods to discover insights automatically. A key advantage is that this approach generalizes to a wide variety of attribute types such as categorical, numerical, and temporal, as well as complex non-trivial combinations of these different attribute types. To evaluate the effectiveness of our approach, we implemented a new insight-centric visualization recommendation system, SpotLight, which generates and ranks annotated visualizations to explain each insight. We conducted a user study with 12 participants and two datasets which showed that users are able to quickly understand and find relevant insights in unfamiliar data.