Co-authors: Suruchi Shah and Hari Shankar The rise of instant messaging has changed how we communicate. Compared to the back-and-forth of email, we send and receive messages at much higher volumes and speeds. In the instant conversations we have, we also expect to be able to search for important phrases, moments, or references with ease. This rapid increase in...
Search Articles
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- Topics:
- Performance,
- infrastructure,
- Architecture,
- Search
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As members explore the many products of LinkedIn, including the feed, homepage, Learning, Recruiter, and Sales Navigator, to name a few, they often experience new exciting features, which, from time to time, may lead to questions around use. To help our members and deliver the assistance they need, we use deep learning-powered Natural Language Processing (NLP)...
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LinkedIn’s Help Center boasts a personalized experience aimed at getting our members the help they need, finding the answers to their questions, and empowering them to be more productive and successful. Despite having a wealth of customized content, members are still faced with a problem when they need help: they must stop what they’re doing and go to the Help...
- Topics:
- trust engineering,
- Search,
- Product Design,
- Ember
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Faceted search is a vital part of LinkedIn’s search experience. It’s a key feature in the exploratory searches done by job seekers,...
- Topics:
- Faceting,
- Galene,
- Information Retrieval,
- infrastructure,
- Search
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LinkedIn started in 2003 with the goal of connecting to your network for better job opportunities. It had only 2,700 members the first...
- Topics:
- scale,
- rest.li,
- Play,
- Open Source,
- Galene,
- Pinot,
- engineering culture,
- ESPRESSO,
- Kafka,
- inversion,
- Architecture,
- Voldemort,
- operations,
- Java,
- Search,
- Samza
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At a recent invitation-only gathering about Search technology hosted by LinkedIn’s Bangalore office, Igor Perisic, VP Engineering at...
- Topics:
- Galene,
- scalability,
- Search,
- Bangalore,
- SNA