Collaborating Authors


Weaviate is an open-source search engine powered by ML, vectors, graphs, and GraphQL


Bob van Luijt's career in technology started at age 15, building websites to help people sell toothbrushes online. Not many 15 year-olds do that. Apparently, this gave van Luijt enough of a head start to arrive at the confluence of technology trends today. Van Luijt went on to study arts but ended up working full time in technology anyway. In 2015, when Google introduced its RankBrain algorithm, the quality of search results jumped up.

10 Applications of Artificial Intelligence in Digital Marketing


Artificial Intelligence has marked its presence in almost every industry and walks of life. It has not only been reducing the human interventions in various operations but also helping humans to do their job better. Fields like Social Media, Consumer Electronics, Robotics, Travel and Transportation, Finance, Healthcare, Security, Surveillance, E-commerce, etc. are already benefiting from AI. Digital Marketing and AI go hand-in-hand. In digital marketing, there is a massive requirement to process tons of data. Artificial Intelligence helps digital marketers to process data faster, which allows them to create digital strategies more efficiently.

Effective Search Engine Optimization Requires a Commitment, Not a Campaign


A successful product and brand strategy develops brand awareness and identity that distinguishes a product from countless others based on just the brand name. A well-crafted strategy repeatedly reminds prospective and existing customers why they should buy a particular product over others with similar characteristics. Brand is just a perception, and perception will match reality over time. A brand is any trade mark through which a product is correctly identified and described by consumers. Therefore, the brand includes any action and remedy by which the product is identified.

Attract a larger audience with this stacked SEO training bundle


TL;DR: The SEO Blueprint for Ranking on Google Bundle is on sale for £29.15 as of March 26, saving you 92% on list price. Digital marketing trends come and go, but there's one thing that never changes: You won't be as relevant if you're not on the first page of Google search, and there's data to back it up. Reports show that 75% of people never bother to scroll past the first page of search results, so regardless of how stellar your content is, barely anyone will see it unless you know what you're doing. We're talking about search engine optimisation (SEO), which is a set of processes that help your site and content skyrocket to the first page and gain relevance. It takes time, energy, and patience to get your SEO in a good place, but the SEO Blueprint Course Bundle can certainly help.

How to Cater to The Next Breed of Shoppers with Artificial Intelligence


Developments in the field of artificial intelligence are incredible, almost as if they are from a different world. Investors spend millions in the development of AI. The most active technology is used in the field of Internet search, helping to shape the Google search engine and handle voice assistant requests. AI becomes more perfect with each passing day. Therefore, there is nothing surprising in the fact that this technology is increasingly being used for online retailers.

4 Ways Marketers Can Start Using AI for Better Results – E Global Soft Solutions


Artificial intelligence is no more the future of marketing; it is pretty much at the moment. Consider all the ways AI technology has already started contributing to our everyday lives. Artificial intelligence is progressively becoming a central part of numerous industries and has various use cases, particularly in marketing. All businesses, big or small, have begun using AI to some extent to upgrade their website, products, and customer experience over time. If reports are to be believed, the top-performing organizations are more than 2x likely than their peers to use AI for marketing purposes.

AI, blockchain, and new ways for everyone to monetize their data - Dataconomy


Breakthroughs in AI and innovations in applying blockchain for personal data control and monetization enable new ways to make money off of personal information that most people currently give away for free. Here we highlight three data science and business model innovations, starting with breakthrough ML technology that learns on the fly. There's an emergent machine learning technology out there that offers a clever new way of finding and classifying unstructured content. In geek-speak, the technology is a vertical, personalized search engine that doesn't require expensive knowledge graphs. In human speak, it's a context-sensitive, human-in-the-loop search engine that uses search criteria and implicit user feedback to recommend high-quality results.

This AI-powered resume builder increases your chances of landing your dream job


You know that the competition will be stiff for that job you've been wanting, and your resume will have to stand out from all the rest for you to have a shot at it. The 2021 Complete Resume Builder Master Class Bundle can not only help you with that, but also with cover letters, interviews, and more. Make 2021 the year to turbocharge your career. For those with Microsoft Word or MacOS Pages, a lifetime subscription to Rezi AI-Powered Resume Writing Software Pro will bring the power of artificial intelligence to all your future resumes and cover letters. It will tailor those to specific job descriptions, using keyword targeting and content analysis, as well as automated reviews.

GCN-ALP: Addressing Matching Collisions in Anchor Link Prediction Artificial Intelligence

Nowadays online users prefer to join multiple social media for the purpose of socialized online service. The problem \textit{anchor link prediction} is formalized to link user data with the common ground on user profile, content and network structure across social networks. Most of the traditional works concentrated on learning matching function with explicit or implicit features on observed user data. However, the low quality of observed user data confuses the judgment on anchor links, resulting in the matching collision problem in practice. In this paper, we explore local structure consistency and then construct a matching graph in order to circumvent matching collisions. Furthermore, we propose graph convolution networks with mini-batch strategy, efficiently solving anchor link prediction on matching graph. The experimental results on three real application scenarios show the great potentials of our proposed method in both prediction accuracy and efficiency. In addition, the visualization of learned embeddings provides us a qualitative way to understand the inference of anchor links on the matching graph.