While we've had weeks of early Black Friday deals already, Thanksgiving has brought additional sales, some of which we expect to continue through Black Friday proper. This has been a trend for the past few years -- if you happen to be online and searching for Black Friday deals a few hours before the day arrives, you can expect at least a handful of solid early sales. And that strategy may pay off this year even more than others as supply chain issues continue to push back shipping estimates. The sooner you grab the items on your gift list, the better the chance they'll arrive on time. To make your search a bit easier, we gathered the best early Black Friday tech deals we could find here.

Products featured in this Mail Best article are independently selected by our shopping writers. If you make a purchase using links on this page, we may earn an affiliate commission. Amazon's Black Friday sale has kicked off, and there are plenty of deals to be enjoyed on everything from home and garden to kids toys. If you're in search of an affordable smart home device, it's worth noting that Amazon's Echo Dot (3rd Gen) Smart Speaker with Alexa is now reduced to just $19.99. Now 50 per cent off its original price, this is just one of the top discounts offered in the sale, which has been running all week with new discounts dropping every day.

Streaming devices are pretty affordable nowadays, but there are some benefits to opting for a more expensive model like the Apple TV 4K. We consider it to be the best high-end streaming box, and right now it's on sale for $160, which is one of the better prices we've seen. Amazon has the device for $169, but an automatically applied coupon will knock the price down to $160 at checkout. Apple modestly upgraded its set-top box this year with the biggest improvement being the new Siri remote. The previous remote that came with the Apple TV 4K was clunky to use, but this new model is a huge improvement. It's larger and has a touch-sensitive directional pad that makes it much easier to swipe and scroll between content on your screen.

We live in a world where robots and robotic technology have become part of our everyday lives. While films such as "Metropolis" and television series like "The Twilight Zone" warned of a world in which our mechanical creations would enslave us, many of us could not envision a day without virtual personal assistants like Siri or the floor-cleaning robotic vacuum Roomba.

If you're in the market for a budget-friendly smart speaker or two (or three) this Black Friday, it might be worth casting a glance in Amazon's direction. Several Echo devices went on sale last week, and now you can save on more. Among them is the Echo Dot with Clock. It's $35 at the moment, which is $25 lower than the regular price and an all-time low. The Echo Dot is a smaller version of the Echo speaker.

The geometry of meaning: Semantics based on conceptual spaces.

Should I buy a Chromebook or a Windows laptop? It's a common question, whether asked by parents weighing the best computer option for back-to-school or by people who just want an inexpensive computer for themselves. We'll help you choose the right one. Our latest update includes more answers to questions you might have: such as, how slow (and inexpensive) can a Chromebook be before it stops being usable? What does Windows 11 and Windows 11 SE mean for laptops? Read on for the answers, plus our up-to-date buying guide for November 2021 and Black Friday, plus more details and what to buy. A notebook PC or laptop powered by Microsoft Windows offers several advantages. Windows offers the most flexibility to run just about any app, your choice of any browser, and configure antivirus options, utilities, and more. You can tweak and configure your PC as you choose. That convenience demands more computing horsepower, and often a higher price compared to most Chromebooks. Prices can soar into the thousands of dollars, and if you need a powerful PC for gaming or video editing, Chromebooks can't compete, and they don't try to. But you'll find some great deals among our more affordably priced, top Windows picks. See our buying guide to the best laptops for even more options.

The Habitat 2.0 simulation platform is for training virtual robots in interactive, physics-enabled 3D environments. We present the new ReplicaCAD 3D data set of apartments; the Habitat 2.0 simulator, capable of simulating 850x faster than real time; and the Home Assistant Benchmark, a suite of common tasks for assistive robots.

Recent advances in path-based explainable recommendation systems have attracted increasing attention thanks to the rich information provided by knowledge graphs. Most existing explainable recommendations only utilize static knowledge graphs and ignore the dynamic user-item evolutions, leading to less convincing and inaccurate explanations. Although there are some works that realize that modelling user's temporal sequential behaviour could boost the performance and explainability of the recommender systems, most of them either only focus on modelling user's sequential interactions within a path or independently and separately of the recommendation mechanism. In this paper, we propose a novel Temporal Meta-path Guided Explainable Recommendation leveraging Reinforcement Learning (TMER-RL), which utilizes reinforcement item-item path modelling between consecutive items with attention mechanisms to sequentially model dynamic user-item evolutions on dynamic knowledge graph for explainable recommendation. Compared with existing works that use heavy recurrent neural networks to model temporal information, we propose simple but effective neural networks to capture users' historical item features and path-based context to characterize the next purchased item. Extensive evaluations of TMER on two real-world datasets show state-of-the-art performance compared against recent strong baselines.

Collaborative filtering (CF) is an important approach for recommendation system which is widely used in a great number of aspects of our life, heavily in the online-based commercial systems. One popular algorithms in CF is the K-nearest neighbors (KNN) algorithm, in which the similarity measures are used to determine nearest neighbors of a user, and thus to quantify the dependency degree between the relative user/item pair. Consequently, CF approach is not just sensitive to the similarity measure, yet it is completely contingent on selection of that measure. While Jaccard - as one of those commonly used similarity measures for CF tasks - concerns the existence of ratings, other numerical measures such as cosine and Pearson concern the magnitude of ratings. Particularly speaking, Jaccard is not a dominant measure, but it is long proven to be an important factor to improve any measure. Therefore, in our continuous efforts to find the most effective similarity measures for CF, this research focuses on proposing new similarity measure via combining Jaccard with several numerical measures. The combined measures would take the advantages of both existence and magnitude. Experimental results on, Movie-lens dataset, showed that the combined measures are preeminent outperforming all single measures over the considered evaluation metrics.