A context-aware recommender system (CARS) applies sensing and analysis of user context to provide personalized services. The contextual information can be driven from sensors in order to improve the accuracy of the recommendations. Yet, generating accurate recommendations is not enough to constitute a useful system from the users' perspective, since certain contextual information may cause different issues, such as draining the user's battery, privacy issues, and more. Adding high-dimensional contextual information may increase both the dimensionality and sparsity of the model. Previous studies suggest reducing the amount of contextual information by selecting the most suitable contextual information using a domain knowledge. Another solution is compressing it into a denser latent space, thus disrupting the ability to explain the recommendation item to the user, and damaging users' trust. In this paper we present an approach for selecting low-dimensional subsets of the contextual information and incorporating them explicitly within CARS. Specifically, we present a novel feature-selection algorithm, based on genetic algorithms (GA), that outperforms SOTA dimensional-reduction CARS algorithms, improves the accuracy and the explainability of the recommendations, and allows for controlling user aspects, such as privacy and battery consumption. Furthermore, we exploit the top subsets that are generated along the evolutionary process, by learning multiple deep context-aware models and applying a stacking technique on them, thus improving the accuracy while remaining at the explicit space. We evaluated our approach on two high-dimensional context-aware datasets driven from smartphones. An empirical analysis of our results validates that our proposed approach outperforms SOTA CARS models while improving transparency and explainability to the user.

In the same way a smart video doorbell keeps a watchful eye over your home, a smart pool water monitor can help keep tabs on the quality of your precious pool water. It may seem like a trivial gadget to add to your home, but if you've spent any time schlepping water from your pool to the pool store every week, you know how time-consuming it can be. And, during a pandemic-riddled summer when social distancing is still in effect, taking matters into your own hands may just be the way to go. I've tried all sorts of smart gadgets before but nothing like the pHin smart pool water monitor. The pHin smart pool water monitor comes neatly packaged and includes everything you need, including a bridge, to set it up.

With Smart Home technology taking off and smart home assistants (like Amazon Alexa, Google Home and Apple Siri) becoming more prevalent in homes the start of a new home technology revolution is underway. Homeowners can monitor and control the house heating and cooling systems, security systems, door locks, garage doors and more all from where ever they have access to internet on their smartphone. Artificial intelligence (AI) will add to that ability by allowing decisions about the home to be made without the need of direct input from the homeowner. For instance a trusted dog walker walks up to the front door during their scheduled time to take Fido out for a walk. The dog walker's face is seen via camera which an artificial intelligence assistant recognizes and knows they are there during the correct time and allows the door to be unlocked so Fido can enjoy some outdoor time while the homeowner is away.

Samsung's phones may be the among the most popular Android handsets, but they're also the furthest from Google's vision, with their own app store, UI, and digital assistant. But with the launch of the Galaxy Note 20 just a week away, a new report from Bloomberg suggests that Google is looking to rein in some of Samsung's freedom. According to correspondence between the two companies, Google is looking to take back search on Samsung's handsets, the foundation for everything Android does. The two companies are discussing a deal that would "promote Google's digital assistant and Play Store for apps" on Galaxy devices. That would be a major change over the current system.

Machine learning is simply a computer learning from data instead of following a recipe. It's meant to mimic how people (and perhaps other animals) learn while still being grounded in mathematics. This post is meant to get you started with a basic machine learning model. Now, we're not re-creating Alexa, Siri, Cortana, or Google Assistant but we are going to create a brand new machine learning program from scratch. This course is meant to be easy assuming you know a bit of Python Programming.

The data contained in dating apps is both very personal and valuable to hackers, who can use it to make highly convincing cyberattacks. So it's always disturbing to learn about dating app security flaws. In a report released today, security research firm CheckPoint Research announced that it found several security vulnerabilities in OKCupid's website and mobile apps. The flaws could have allowed hackers to access users' full profile details, private messages, personal addresses and more. Hackers could even send messages from their victims' profiles.

Executives from NVIDIA, Deepgram, and Sharpen gathered via Zoom on Wednesday to discuss the current state of the voice tech industry, as well as where it's going. Growth in artificial intelligence (AI) technology and machine learning have had a huge hand in lifting the market, but it's only the beginning. Voice tech has seen rapid growth in recent years and isn't predicted to stop: The market is estimated to be worth nearly $32 billion by 2025, a Grand View Research report found. With smart speakers and home assistants like Amazon Alexa, Apple's Siri, and Google Assistant making voice tech mainstream, most consumers are familiar with the concept. However, the technology is more complex than people may think and it has come a long way.

A couple of the newest TCL Roku TVs are back on sale again at Best Buy. The last time we saw a sale on the 8-series sets was around the July 4th holiday, but you can get an even better deal on one of those TVs now. The 65-inch TCL 8-series Roku TV is $1,000 right now, which is 50 percent off its normal price, but the massive 75-inch TCL 8-series Roku TV dropped to $1,500. That's 50 percent off and $300 cheaper than it was during the previous sale. These TCL TVs came out at the end of 2019 and they made a splash for their use of quantum-dot LED and mini LED technology.

Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount of training data. The large model size usually entails a cost, in the range of millions of dollars, for storage and communication with the inference services. In this paper, we propose a hybrid hashing method to combine frequency hashing and double hashing techniques for model size reduction, without compromising performance. We evaluate the proposed models on two product surfaces. In both cases, experiment results demonstrated that we can reduce the model size by around 90 % while keeping the performance on par with the original baselines.

The leadership change at Match Group’s flagship dating app comes as the coronavirus pandemic is redefining the online dating industry.