Recommender systems recommend items more accurately by analyzing users' potential interest on different brands' items. In conjunction with users' rating similarity, the presence of users' implicit feedbacks like clicking items, viewing items specifications, watching videos etc. have been proved to be helpful for learning users' embedding, that helps better rating prediction of users. Most existing recommender systems focus on modeling of ratings and implicit feedbacks ignoring users' explicit feedbacks. Explicit feedbacks can be used to validate the reliability of the particular users and can be used to learn about the users' characteristic. Users' characteristic mean what type of reviewers they are. In this paper, we explore three different models for recommendation with more accuracy focusing on users' explicit feedbacks and implicit feedbacks. First one is RHC-PMF that predicts users' rating more accurately based on user's three explicit feedbacks (rating, helpfulness score and centrality) and second one is RV-PMF, where user's implicit feedback (view relationship) is considered. Last one is RHCV-PMF, where both type of feedbacks are considered. In this model users' explicit feedbacks' similarity indicate the similarity of their reliability and characteristic and implicit feedback's similarity indicates their preference similarity. Extensive experiments on real world dataset, i.e. Amazon.com online review dataset shows that our models perform better compare to base-line models in term of users' rating prediction. RHCV-PMF model also performs better rating prediction compare to baseline models for cold start users and cold start items.

There is no denying the fact that technology and automation have rapidly transformed the way business is done. The rise of Artificial Intelligence (AI), in particular, has given rise to interesting speculations about how rapidly robots will take over the workplace. Customer-facing industries have jumped on the chatbots bandwagon almost as soon as they arrived into the market. The results have been increased efficiencies and reduced costs, especially in customer service functions. It is no surprise then that businesses across a plethora of industries are looking into how they too can adopt chatbots and what it can mean for their business outcomes.

The Black Friday shopping event is a great chance to grab a bargain, but it can also open up golden opportunities for scammers and hackers. With deals constantly launching and expiring, you'll need to move quickly in order to get what you want. However, you still need to take the right measures to ensure you're not being duped. Here are some useful tips worth following this Black Friday. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Amazon has been pretty busy the past few months, unleashing a slew of new hardware just in time for the holiday season. Several of those products haven't made it to market quite just yet, but that hasn't stopped the company from raking in money as per usual. In its third quarterly earnings report, Amazon reported that net sales in the past three months have totaled $56.6 billion, which is a 30 percent year-over-year increase. Meanwhile, net income has increased to $2.9 billion in the third quarter, which is a big jump from the $256 million from this time last year. This is the 14th straight quarter that the online retail giant has reported a profit. That said, the numbers are below Wall Street estimates and the stock dropped by 6 percent as earnings came in.

Large retailers have found that the quickest way to get access to new products and technologies is to invest – and in some cases to accelerate or incubate – in the startups that are creating them. Some of the startups are focused on technology, and others on product. This is H&M's second such investment this month, following the $20 million it paid for a 1% stake in fintech startup Klarna last week. Target has been prominent among other retailers cultivating startups, first with its Target Techstars accelerator, which recently ran its third annual program. It has expanded into wellness and beauty mini accelerators, and just announced a new accelerator for Gen Z entrepreneurs and creators.

But the deals are here already. The Black Friday phenomenon – which already stretches over the following weekend and into Cyber Monday – grows each year, taking up more days and more focus. That is matched by companies who are more and more desperate to show off their deals, including Amazon. This year, the company has launched its Black Friday page with eight days left to go. And as ever, the best deals look to be on Amazon's own stuff.

Since 2013, more than $17 billion in CPG industry sales have shifted from large players to small ones. Size used to be one of the most important factors of success, but e-commerce has leveled the playing field, subsequently allowing smaller brands to reach consumers in unprecedented ways. The latest IRI Point of View, "The Next Frontier: Leveraging Artificial Intelligence and Unstructured Metrics to Identify CPG Growth Pockets and Outperforming Brands," identifies how to gain an edge by identifying where to play; whom to buy or draw inspiration from; and how to use a set of nontraditional, unstructured metrics and artificial intelligence to predict areas that will become future growth pockets before they manifest themselves among the traditional measured channels. "Given the current climate where CPG manufacturers are struggling to expand, identifying attractive, sustainable pockets of growth and outperforming brands can be a game changer," said Jamil Satchu, partner and practice leader, IRI Growth Consulting. "Accurately identifying and then prioritizing pockets enables growth teams with a powerful road map for future investment and acquisition activity."

Infrared light flooded down invisibly as I eyed the pastries in Amazon's new convenience store in downtown San Francisco. It helped cameras mounted on the store's ceiling detect that I picked up a croissant, then put it back. My flirtation with a $3.19 morsel of flaky pastry was recorded during a preview of the Amazon Go store that opened in San Francisco's financial district this morning. As in the five other such stores in Seattle and Chicago, shoppers gain entry by scanning a QR code in the Amazon Go mobile app to open a subway-style entry gate. Hundreds of cameras on the ceiling, plus sensors in the shelves, then record what each person picks up, so they can walk out without having to visit a checkout.

Futurists say in-store shopping experiences will be highly personalized before too long. Salespeople will know your likes and dislikes seemingly off the top of their heads, and they'll know to highlight the items you're most likely to find attractive. Artificial intelligence (AI) can help drive that kind of bespoke experience, and Mystore-E intends to establish an early foothold in the market with an adaptable, on-premise platform designed for retail outlets. It's well on its way: The two-year-old Tel Aviv startup recently raised $2.2 million in a seed round and secured an exclusive partnership with Signet Jewelers. "Mystore-E cares deeply about the future of … shopping," CEO Asaf Shapira said. "Our goal is to create a personalized shopping experience that benefits retail stores, while also catering to the customers' wants, needs, and style preferences."

This article is from today's FT Opinion email. Sign up to receive a daily digest of the big issues straight to your inbox. The giant US retailer Sears, the "everything store", offers a cautionary tale about how companies across the sector have failed to keep ahead of their customers' needs and shopping behaviour. For Andrew Edgecliffe-Johnson, who explores the company's bankruptcy filing in a column this week, it is not just a sad tale of a once-great American business fallen on hard times. The demise of the "19th-century offline Amazon", as Andrew describes it, is a warning to those other companies who have failed to come up with adequate strategies in response to the online retail threat.