Semantic Indexing: Google's Big Data Trick For Multilingual Search Results

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Google has perfected its ability to execute web search results for its users all over the world. In the early days of the Internet, the search engine was primarily suited for displaying search results for English users. Non-English-speaking users have complained that search results are often displayed in the wrong language entirely. However, Google is becoming more proficient at providing search results in other languages as well. A lot of factors can play a role, but one of the biggest is its use of deep learning to understand semantic references--enter semantic indexing.


How big data is changing science

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"This is when I start feeling my age," says Anne Corcoran. Corcoran leads a group that looks at how our genomes – the DNA coiled in almost every cell in our bodies – relate to our immune systems, and specifically to the antibodies we make to defend against infection. She is, in her own words, an "old-school biologist," brought up on the skills of pipettes and Petri dishes and protective goggles, the science of experiments with glassware on benches – what's known as "wet lab" work. "I knew what a gene looked like on a gel," she says, thinking back to her early career. These days that skill set is not enough. "When I started hiring Ph.D. students 15 years ago, they were entirely wet lab," Corcoran says. "Now when we recruit them, the first thing we look for is if they can cope with complex bioinformatic analysis." To be a biologist, nowadays, you need to be a statistician, or even a programmer.


Studying genetics in the age of big data

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New biomedical techniques, such as next-generation genome sequencing, are creating vast amounts of data and transforming the scientific landscape. They're leading to unimaginable breakthroughs -- but leaving researchers racing to keep up. "This is when I start feeling my age," Anne Corcoran says. Corcoran leads a group that looks at how our genomes -- the DNA coiled in almost every cell in our bodies -- relate to our immune systems, and specifically to the antibodies we make to defend against infection. She is, in her own words, an "old-school biologist," brought up on the skills of pipettes and Petri dishes and protective goggles, the science of experiments with glassware on benches -- what's known as'wet lab' work. "I knew what a gene looked like on a gel," she says, thinking back to her early career. These days, that skill set is not enough. "When I started hiring Ph.D. students 15 years ago, they were entirely wet lab," Corcoran says. "Now when we recruit them, the first thing we look for is if they can cope with complex bioinformatic analysis."


How Big Data Is Changing Science

#artificialintelligence

She is, in her own words, an "old-school biologist", brought up on the skills of pipettes and Petri dishes and protective goggles, the science of experiments with glassware on benches – what's known as "wet lab" work. "I knew what a gene looked like on a gel," she says, thinking back to her early career. These days that skill set is not enough. "When I started hiring PhD students 15 years ago, they were entirely wet lab," Corcoran says. "Now when we recruit them, the first thing we look for is if they can cope with complex bioinformatic analysis." To be a biologist, nowadays, you need to be a statistician, or even a programmer. You need to be able to work with algorithms. An algorithm, essentially, is a set of instructions – a series of predefined steps.


Amazon.com: Entity Information Life Cycle for Big Data: Master Data Management and Information Integration (9780128005378): John R. Talburt, Yinle Zhou: Books

@machinelearnbot

The authors have done an excellent job tying together state of the art academic concepts with state of the practice business needs, showing clearly how these two (much hyped) concepts can be used to provide value to our organizations. A must read for anyone confused about how to apply these concepts ...