The increasing reliance on online communities for healthcare information by patients and caregivers has led to the increase in the spread of misinformation, or subjective, anecdotal and inaccurate or non-specific recommendations, which, if acted on, could cause serious harm to the patients. Hence, there is an urgent need to connect users with accurate and tailored health information in a timely manner to prevent such harm. This paper proposes an innovative approach to suggesting reliable information to participants in online communities as they move through different stages in their disease or treatment. We hypothesize that patients with similar histories of disease progression or course of treatment would have similar information needs at comparable stages. Specifically, we pose the problem of predicting topic tags or keywords that describe the future information needs of users based on their profiles, traces of their online interactions within the community (past posts, replies) and the profiles and traces of online interactions of other users with similar profiles and similar traces of past interaction with the target users. The result is a variant of the collaborative information filtering or recommendation system tailored to the needs of users of online health communities. We report results of our experiments on an expert curated data set which demonstrate the superiority of the proposed approach over the state of the art baselines with respect to accurate and timely prediction of topic tags (and hence information sources of interest).

This article was published as a part of the Data Science Blogathon. You must have seen streaming services such as Spotify, Deezer, and Apple Music. So, what better way to flex our backend skills than to work with MongoDB to create our own Spotify backend clone, all with NodeJS? In this article, I will show you how to handle uploading songs to the database, streaming music, user authentication, the ability to choose your favorite songs, and a recommendation engine using machine learning. First up, here is how to set up MongoDB Atlas for NodeJS. You can either register with your email address or use a GitHub or Google account to log in. Enter the new project name and click Next.

A Canadian start-up has developed a voice imitation programme capable of mimicking a person's voice after just a minute of listening to them speak. Developed by AI firm Lyrebird, the algorithm uses machine learning to synthesise speech based on audio samples and is even able to replicate emotion. Lyrebird's algorithm is capable of generating new voices from scratch as well as replicating those of others. After hearing an audio clip, the programme determines the defining feature or "key" to the person's voice and then uses this to generate words from scratch. It even varies the intonations it applies so that a repeated sentence doesn't sound the same way twice.

Amazon was quick to pledge support for the Matter smart home standard, and now it's clear just when (and if) you can expect the technology to reach your household. The company has confirmed that 17 Echo devices, plugs, switches and bulbs will support Matter over WiFi in December, with 30 Echo and Eero products offering support by early next year. You'll initially need Android to set this up (Apple only released the Matter-friendly iOS 16.1 days ago), and the focus will be on lighting. However, support for iOS, Thread and more smart home tech is also due in early 2023. The support will extend to years-old Echo products.

When you think of artificial intelligence (AI), you probably think of human-looking robots. Maybe a bit of fear mixed with a pinch of excitement. Whatever you think of, you most likely don't pair it with marketing. The thing is, you can. AI can improve the customer experience and handle your data more efficiently. Plus, as a bonus, it just sounds cool.

If you thought Alexa was only there to tell you the weather or who scored in the football, think again. Amazon now envisions its virtual assistant becoming a'trusted adviser and companion', and'anticipating' what we want to do, according to its chief scientist. Speaking at the Web Summit in Lisbon yesterday, Rohit Prasad said: 'If I ask Alexa, what hike should I do? Just like a friend, because it knows me, Alexa should tell me: you should do this hike.' The tech giant is envisioning a home with various sensors in each room - from microphones to ultrasound - working in the background, he said.

Digital human recommendation system has been developed to help customers find their favorite products and is playing an active role in various recommendation contexts. How to timely catch and learn the dynamics of the preferences of the customers, while meeting their exact requirements, becomes crucial in the digital human recommendation domain. We design a novel practical digital human interactive recommendation agent framework based on Reinforcement Learning(RL) to improve the efficiency of the interactive recommendation decision-making by leveraging both the digital human features and the superior flexibility of RL. Our proposed framework learns through real-time interactions between the digital human and customers dynamically through the state-of-the-art RL algorithms, combined with multi-modal embedding and graph embedding, to improve the accuracy of personalization and thus enable the digital human agent to timely catch the attention of the customer. Experiments on real business data demonstrate that our framework can provide better personalized customer engagement and better customer experiences.

In particular, it said weaker economic conditions are weighing on brands such as Plenty of Fish, which cater to people with lower incomes, while people were starting to make fewer in-app purchases on its platforms.

For those reasons, you probably shouldn't keep an Echo with this feature in your home office, or anywhere with a lot of devices trying to do things at the same time. If one of your gadgets does latch onto the speaker's network, you may wind up with a limit on your internet performance without even realizing the switch has been made.

Kids love to use smart speakers, but it's all too easy for things to go horribly wrong -- including content that's decidedly not family-friendly. Google is trying to address those worries by both revising parental controls for Assistant and providing more child-oriented responses. To start, an update will let you disable some Assistant features, restrict the services children can use and establish downtime hours. You can bar kids from making calls, or limit them to watching YouTube Kids on a Nest Hub. The controls will be available in the "coming weeks" through the Google Assistant, Google Home and Family Link apps for Android and iOS.