Nowadays, privacy preserving machine learning has been drawing much attention in both industry and academy. Meanwhile, recommender systems have been extensively adopted by many commercial platforms (e.g. Amazon) and they are mainly built based on user-item interactions. Besides, social platforms (e.g. Facebook) have rich resources of user social information. It is well known that social information, which is rich on social platforms such as Facebook, are useful to recommender systems. It is anticipated to combine the social information with the user-item ratings to improve the overall recommendation performance. Most existing recommendation models are built based on the assumptions that the social information are available. However, different platforms are usually reluctant to (or cannot) share their data due to certain concerns. In this paper, we first propose a SEcure SOcial RECommendation (SeSoRec) framework which can (1) collaboratively mine knowledge from social platform to improve the recommendation performance of the rating platform, and (2) securely keep the raw data of both platforms. We then propose a Secret Sharing based Matrix Multiplication (SSMM) protocol to optimize SeSoRec and prove its correctness and security theoretically. By applying minibatch gradient descent, SeSoRec has linear time complexities in terms of both computation and communication. The comprehensive experimental results on three real-world datasets demonstrate the effectiveness of our proposed SeSoRec and SSMM.

"Hey Google, read this page." That's a new command for the Google Assistant that will see the robot reading web pages aloud. Use cases: catching on news that doesn't have a podcast component while driving, having pages translated to you in other languages (say if you're traveling) or just general help for people who are vision-impaired. Fine print: The feature is only available, starting today, on Google's Android smartphone platform. Whenever a web article is displayed on your browser in your Android phone, you can say, "Hey Google, read it" or "Hey Google, read this page" it will immediately read aloud the content of the web page," says Yossi Matias, a Google vice-president. "And to help people follow along at a convenient pace without having to touch the screen, your browser will highlight the words being read out and auto-scroll the page.

Deciding who picks up the bill on a first date may be a cinch for some lucky users of the dating app, Hinge. According to the company, it will award up to 2,500 of its users a $100 Visa gift card that can be used to pay for a date in a bid to help them'unplug' from their phones and meet someone in-person. To activate the promotion, users must pause their profiles from 4 pm on Friday March 6th until Saturday March 7th, during which time they're expected to go on a date. After the two parties go on their date, they're then asked to go into the Hinge app and confirm that they actually attended the meetup up by clicking on their date's profile and selecting'met'. The daters are then asked to say whether they would go on another date with each other and are then are allowed to file for the Visa card on unplugwithhinge.com.

Tinder has posted a warning for its users telling them that coronavirus safety is'more important' than dating and urging them to wash their hands frequently. The dating app also encourages its singletons to carry hand sanitiser, avoid touching their face and'maintain social distance' when out in public. The warning says: 'Tinder is a great place to meet new people. While we want you to continue to have fun, protecting yourself from the coronavirus is more important'. It appears as a pop up while users are flipping between potential matches to warn of the dangers of the potentially deadly virus now called COVID-19. The pop-up warning also includes a link to the latest advice and information from the World Health Organisation (WHO) website.

The result: eBay's copywriters are now able to devote more time to more creative work, such as crafting prose, according to Molly Prosser, associate creative director at eBay and a big believer in AI writing tools. "All the time I've spent lingering over the length of a subject line, wondering'Is this word more engaging, or is this word more engaging', or'How do I convey urgency without seeming too cliché'," says Prosser. "The hours I've spent editing and having team members pour over these things -- it's just meaningless work when we have a piece of AI that can do that for us. The new capability enables Naylor to offer a personalized newsletter for each association member it services -- based on his or her interests and reading habits. The AI tool incorporates personalized content that Naylor generates in-house, as well as content it finds on the Web –including job ads that match the specific job skills of the reader. Essentially, AI enables newsletters to become ever-more personalized over time by monitoring how each reader interacts with his or her personalized newsletter, and making adjustments accordingly, says Amith Nagaranjan, executive chairman, Rasa.io.

Artificial Intelligence (AI) seems to be a unique technology of making a machine, a robot fully autonomous. AI is an analysis of how the machine is thinking, studying, determining and functioning when it is trying to solve problems. These so-called problems are present in all fields - the most emerging ones in 2020 and even beyond. The aim of Artificial Intelligence (AI) is to enhance machine functions relating to human knowledge, such as reasoning, learning and problems along with the ability to manipulate things. For example, virtual assistants or chatbots offer expert advice.

ClickZ spoke with Gonca Latif-Schmitt, Managing Director at Citi, to discuss their technologically-savvy approach to improving customer experience (CX) for their business card holders and clients. Citi engaged work with Interactions for their Citi Commercial Card initiative. Interactions is a provider of intelligent virtual assistants (IVAs) focused on helping companies improve CX via the use of AI chatbot technology. They offers several products that fall within the customer experience space, including an IVA tool utilized by leading brands such as Hyatt, Constant Contact, and Shutterfly. As a credit card business within Citi's institutional group, the commercial card team is focused on making the entire client experience frictionless and more digital.

We consider the problem faced by a recommender system which seeks to offer a user with unknown preferences an item. Before making a recommendation, the system has the opportunity to elicit the user's preferences by making queries. Each query corresponds to a pairwise comparison between items. We take the point of view of either a risk averse or regret averse recommender system which only possess set-based information on the user utility function. We investigate: a) an offline elicitation setting, where all queries are made at once, and b) an online elicitation setting, where queries are selected sequentially over time. We propose exact robust optimization formulations of these problems which integrate the elicitation and recommendation phases and study the complexity of these problems. For the offline case, where the problem takes the form of a two-stage robust optimization problem with decision-dependent information discovery, we provide an enumeration-based algorithm and also an equivalent reformulation in the form of a mixed-binary linear program which we solve via column-and-constraint generation. For the online setting, where the problem takes the form of a multi-stage robust optimization problem with decision-dependent information discovery, we propose a conservative solution approach. We evaluate the performance of our methods on both synthetic data and real data from the Homeless Management Information System. We simulate elicitation of the preferences of policy-makers in terms of characteristics of housing allocation policies to better match individuals experiencing homelessness to scarce housing resources. Our framework is shown to outperform the state-of-the-art techniques from the literature.

The ubiquity of smart phones and electronic devices has placed a wealth of information at the fingertips of consumers as well as creators of digital content. This has led to millions of notifications being issued each second from alerts about posted YouTube videos to tweets, emails and personal messages. Adding work related notifications and we can see how quickly the number of notifications increases. Not only does this cause reduced productivity and concentration but has also been shown to cause alert fatigue. This condition makes users desensitized to notifications, causing them to ignore or miss important alerts. Depending on what domain users work in, the cost of missing a notification can vary from a mere inconvenience to life and death. Therefore, in this work, we propose an alert and notification framework that intelligently issues, suppresses and aggregates notifications, based on event severity, user preferences, or schedules, to minimize the need for users to ignore, or snooze their notifications and potentially forget about addressing important ones. Our framework can be deployed as a backend service, but is better suited to be integrated into proactive conversational agents, a field receiving a lot of attention with the digital transformation era, email services, news services and others. However, the main challenge lies in developing the right machine learning algorithms that can learn models from a wide set of users while customizing these models to individual users' preferences.

SearchAI Answers is an Artificial Intelligence as a Service (AIaaS) service from SearchBlox that offers direct answers to natural language search queries using an AI model built using the customers' content, without the need for any manual tagging or a domain specific taxonomy or creating a knowledge graph. Search Engines as Question Answering (QA) Engines will replace the traditional approach of information retrieval where we are presented with a list of search results links. What is driving the transformation from search to answers? • New generation of searchers using Siri, Echo & Google Assistant using voice as a primary channel of getting information • Want to ask direct questions and receive direct answers • Ask questions in natural language or a conversational manner • Need concise, relevant and context based domain specific answers SearchAI Answers use explicit and implicit feedback to continually improve the quality of answers using MLOps. What are the business benefits of using SearchAI Answers on your website or portal? Contact us to get started and we will have you running our AI service very quickly.