The Preferences for Everyday Living Inventory (PELI) is a 72-question instrument used for helping nursing homes assess person-centered care. In particular, the approach allows residents to express their preferences for both care and activities in order to provide direct care workers with insights on how to best provide a high-quality living experience. Among the challenges of using the PELI is its length: 72 questions give rise to issues of survey fatigue while also creating a workflow bottleneck for those providing care. In this paper we explore and evaluate the use of three different recommender strategies that we have applied to the PELI. In particular, we present the use of both rule-based and neighborhood-based collaborative filtering in order to make recommendations on which preference questions to present to a resident. We illustrate the approaches by providing a domain-specific example, and then compare the approaches across a number of performance and quality metrics.

Google is facing an onset of privacy concerns after it announced it plans to dissolve the Nest brand in favor of a new, all-purpose smart home division, called Google Nest. As part of the decision, existing users of Nest smart thermostats, security cameras and other products will be forced to migrate their information over to a Google account. The announcement, made at Google's I/O developer conference last week, has caught the eye of some users and experts who say it gives them little control over the future of their Nest data and, as a result, their privacy. When Google acquired Nest in 2014 for $3.2 billion, Nest pledged to keep the data it collects on its users separate from Googles other services. 'When you work with Nest and use Nest products, that data does not go into the greater Google or any of its other business units,' Tony Fadell, former CEO of Nest, told BBC in 2015.

Alexa's got a new gig: home safety. Amazon today introduces Alexa Guard, a free feature that uses the microphones of the Amazon Echo speakers to listen for the sounds of smoke and carbon monoxide alarms or breaking glass. Should the personal assistant hear any of those, it will send text alerts to your phone. Amazon says it's introducing the feature to "help you keep your home safe." Amazon says that security devices, such as the Ring video doorbell, which Amazon owns, or ADT Pulse, which it doesn't, can work with Guard in that Alexa will send the alerts to the security provider. Additionally, Alexa can be programmed to have smart, connected lights turn on and off remotely when you're out "to make it look like you're home while you're away," says Amazon.

The Like other social systems, in collaborative filtering a small number main tenet of this approach is to recommend items of interest to a of "influential" users may have a large impact on the recommendations user based on the preferences of other similar users in the system. of other users, thus affecting the overall behavior of the Because of the social nature of these systems, a small group of system. Identifying influential users and studying their impact on "influential" users can have a significant impact on the behavior other users is an important problem because it provides insight of the system towards other users. This type of influence may, in into how small groups can inadvertently or intentionally affect the some cases, result in undesirable effects such as bias toward certain behavior of the system as a whole. Modeling these influences can items, lack of diversity or imbalance in recommendations, and even also shed light on patterns and relationships that would otherwise potential security concerns such as making it easier to deliberately be difficult to discern, hopefully leading to more transparency in manipulate the system outcomes.

The most buzzed-about disruptive technologies that are changing business landscapes today are Machine Learning (ML) and Artificial Intelligence (AI). Almost all of us have heard or read about them but do we actually know what the fuss is all about? The enterprises are trying to harness the explosion of digital data and computational power with advanced algorithms to enable collaborative and natural interactions between people and machines. However, there's still a lot of confusion within the public and the media regarding what is ML and AI. People prefer to write AL and ML technologies -- and not ML and AI -- and the argument goes that the former syncs well with the human mind.

It's pretty obvious that just about everyone uses a smartphone to help assist with their day to day activities. Smartphones have evolved from being just a communication tool to a highly effective business tool over the years. The importance of Mobile Apps in Business has grown significantly in the past few years. More specifically, the younger generation has more capability to interact with e-business. Mobile apps have made it easier for users to get any business's information with the touch of a finger and stay connected to their favorite brands.

Artificial intelligence was first thought of in the 1950s, but it was only since the 90s that any real progress was made. Today, AI has filtered through the market chain and is now available as a consumer product in the form of virtual assistants like Siri and Alexa. Despite the great interest in the field, AI hasn't grown as fast as other technologies over the decades.

The most buzzed-about disruptive technologies that are changing business landscapes today are Machine Learning (ML) and Artificial Intelligence (AI). Almost all of us have heard or read about them but do we actually know what the fuss is all about? The enterprises are trying to harness the explosion of digital data and computational power with advanced algorithms to enable collaborative and natural interactions between people and machines. However, there's still a lot of confusion within the public and the media regarding what is ML and AI. People prefer to write AL and ML technologies -- and not ML and AI -- and the argument goes that the former syncs well with the human mind.

Last week, Anki, creator of adorable robots that are part toy, part virtual assistant and part pet, went out of business. "It is with a heavy heart to inform you that Anki has ceased product development and we are no longer manufacturing robots," the company said in a statement, which promised to help owners keep enjoying their little mechanical pals for as long as possible. Why did Anki – a company that had attracted a huge amount of funding and interest in its earlier days – find itself so strapped for cash that it had to pull the plug? Vector's expressions were designed by a professional character artist (Image credit: Anki) Robot vacuum cleaners are one thing – we might feel a little affection towards them, but they're very utilitarian. When it comes to robots for fun and companionship, we're much more hesitant.

Last week, Anki, creator of adorable robots that are part toy, part virtual assistant and part pet, went out of business. "It is with a heavy heart to inform you that Anki has ceased product development and we are no longer manufacturing robots," the company said in a statement, which promised to help owners keep enjoying their little mechanical pals for as long as possible. Why did Anki – a company that had attracted a huge amount of funding and interest in its earlier days – find itself so strapped for cash that it had to pull the plug? Vector's expressions were designed by a professional character artist (Image credit: Anki) Robot vacuum cleaners are one thing – we might feel a little affection towards them, but they're very utilitarian. When it comes to robots for fun and companionship, we're much more hesitant.