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In information retrieval, Okapi BM25 (BM stands for Best Matching) is a ranking function used by search engines to rank matching documents according to their relevance to a given search query. It is based on the probabilistic retrieval framework developed in the 1970s and 1980s by Stephen E. Robertson, Karen Spärck Jones, and others.

The name of the actual ranking function is BM25. To set the right context, however, it is usually referred to as "Okapi BM25", since the Okapi information retrieval system, implemented at London's City University in the 1980s and 1990s, was the first system to implement this function.

BM25 and its newer variants, e.g. BM25F (a version of BM25 that can take document structure and anchor text into account), represent state-of-the-art TF-IDF-like retrieval functions used in document retrieval.


https://en.wikipedia.org/wiki/Okapi_BM25
https://inyl.github.io/search_engine/2017/04/01/bm25.html
https://www.slideshare.net/kjmorc/ss-80803233
2018/01/03 12:09 2018/01/03 12:09
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About Abseil

Abseil is an open-source collection of C++ library code designed to augment the C++ standard library. The Abseil library code is collected from Google’s own C++ code base, has been extensively tested and used in production, and is the same code we depend on in our daily coding lives.

In some cases, Abseil provides pieces missing from the C++ standard; in others, Abseil provides alternatives to the standard for special needs we’ve found through usage in the Google code base. We denote those cases clearly within the library code we provide you.

Abseil is not meant to be competitor to any standard library code; we’ve just found that many of these utilities serve a purpose within our code base, and we now want to provide those resources to the C++ community as a whole.

https://abseil.io/

2018/01/03 11:21 2018/01/03 11:21
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분류없음  2018/01/03 11:03
C++ Conference

https://cppcon.org/cppcon-2017-program/
2018/01/03 11:03 2018/01/03 11:03
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The tl;dr

We should all be automating our image compression.

In 2017, image optimization should be automated. It's easy to forget, best practices change, and content that doesn't go through a build pipeline can easily slip. To automate: Use imagemin or libvips for your build process. Many alternatives exist.

Most CDNs (e.g. Akamai) and third-party solutions like Cloudinary, imgix, Fastly's Image Optimizer, Instart Logic's SmartVision or ImageOptim API offer comprehensive automated image optimization solutions.

The amount of time you'll spend reading blog posts and tweaking your configuration is greater than the monthly fee for a service (Cloudinary has a free tier). If you don't want to outsource this work for cost or latency concerns, the open-source options above are solid. Projects like Imageflow or Thumbor enable self-hosted alternatives.


https://images.guide/
2018/01/03 10:58 2018/01/03 10:58
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https://eng.uber.com/

2018/01/03 10:24 2018/01/03 10:24
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