Our accustomed systems of retrieving particular bits of information no longer fill the needs of many people. Searching traditional indexes of print publications has been aided by computerized databases, but still usually requires time-consuming serial searching of one database after the other, and then moving on to other methods of searching for internet sources. And what if the information being sought is a sound byte? A video clip? Yesterday's e-mail exchange between respected scientists? Artificial intelligence may hold the key to information retrieval in an age where widely different formats contain the information being sought, and the universe of knowledge is simply too big and growing too rapidly for successful searching to proceed at a human's slow speed.
Instagram is introducing a new way to showcase local businesses with in-app profile pages. Raj Nijjer alerted me to this feature while providing several screenshots. As you can see in the examples below, the pages look very much like Google local knowledge panels. They have the business address, hours, contact information, and website. Of course, a link to the business's Instagram profile is featured prominently at the top of the page.
Myth: "The customer journey is not as complex as it's made out to be." One thing is for sure – the consumer decision journey is more complex than ever before. The average consumer now owns three to four devices and uses multiple online and offline channels throughout their shopping journeys. The game is changing as marketers turn to artificial intelligence, agencies and data to help them navigate new consumer behavior. Every marketer today needs to be addressing these challenges as the CDJ itself is disrupting the digital landscape.
Knowing exactly who your customers are is an important task for security, fraud detection, marketing, and personalization. The proliferation of data sources and services has made ER very challenging in the internet age. In addition, many applications now increasingly require near real-time entity resolution.
While we love our smartphones, they are vulnerable to hackers. Here are some ways to keep them hacker free. Some people think they're immune to cybercriminals. "I'm not even on their radar," they think. "What are the chances that I'll get targeted? It's not like I'm famous or have zillions of dollars."
Advancements under the moniker of the Internet of Things (IoT) allow things to network and become the primary producers of data in the Internet.14 IoT makes the state and interactions of real-world available to Web applications and information systems with minimal latency and complexity.25 By enabling massive telemetry and individual addressing of "things," the IoT offers three prominent benefits: spatial and temporal traceability of individual real-world objects for thief prevention, counterfeit product detection and food safety via accessing their pedigree; enabling ambient data collection and analytics for optimizing crop planning, enabling telemedicine and assisted living; and supporting real-time reactive systems such as smart building, automatic logistics and self-driving, networked cars.11 Realizing these benefits requires the ability to discover and resolve queries for contents in the IoT. Offering these abilities is the responsibility of a class of software system called the Internet of Things search engine (IoTSE).
Algorithms, computation and visual data are the three pillars of computer vision (CV). Researchers, institutions and open source communities have produced sophisticated algorithms and open-sourced code; while global tech giants' supercharged cloud platforms provide all the computational power CV researchers require. However, efficiently sourcing visual data -- particularly images with high-quality annotations -- remains a challenge. Building large datasets is a time-consuming and labor-intensive task which challenges entities with limited budgets. There are hundreds of open visual datasets out there, but searching across them and their millions of entries is not a simple task.
In Search Engine Optimization All-in-One For Dummies, 3rd Edition, Bruce Clay--whose search engine consultancy predates Google--shares everything you need to know about SEO. In minibooks that cover the entire topic, you'll discover how search engines work, how to apply effective keyword strategies, ways to use SEO to position yourself competitively, the latest on international SEO practices, and more. If SEO makes your head spin, this no-nonsense guide makes it easier. You'll get the lowdown on how to use search engine optimization to improve the quality and volume of traffic on your website via search engine results. Cutting through technical jargon, it gets you up to speed quickly on how to use SEO to get your website in the top of the rankings, target different kinds of searches, and win more industry-specific vertical search engine results!
The task of maintaining a WordPress site needs consistency and tenacity in order to have a profitable enterprise. This task might become a herculean one, time-consuming and an excruciating one if you are to work manually on all the WordPress plug-ins without any assistance. But with the advent of Artificial Intelligence (AI), most of the tasks on these WordPress plug-ins are thus simplified with the help of AI boosting the quality of your WordPress site and in turn, increasing your profitability. This is part I of the two-part articles. For the second part please check this link.
The research surrounding methods of information retrieval is an entire field of science whose specialists aim to provide us with even better search results – a necessity as the amount of data constantly keeps growing. To succeed in their quest, researchers are focusing on the interaction between humans and computers, connecting methods of machine learning to this interaction. One of these researchers is Dorota Głowacka, who assumed an assistant professorship in machine learning and data science at the Helsinki Centre for Data Science HiDATA at the beginning of 2019. Głowacka is studying what people search for and how they interact with search engines, with a particular focus on exploratory search. This is a search method that helps find matters relevant to the person looking for information, even if they are not entirely certain about what they are looking for to begin with.
I am a senior data scientist at LinkedIn working on SEO and guest experience. I presented at SMX London last month about how to apply data science in SEO. The session covered topics including metrics, A/B testing, SEO vs. SEM cannibalization testing and machine learning for content quality. Here are a few questions from session attendees with my responses. For A/B testing, do you use any specific tools/processes?