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Approximate nearest neighbor search (ANNS) constitutes an important operation in a multitude of applications, including recommendation systems, information retrieval, and pattern recognition. In the past decade, graph-based ANNS algorithms have been the leading paradigm in this domain, with dozens of graph-based ANNS algorithms proposed. Such algorithms aim to provide effective, efficient solutions for retrieving the nearest neighbors for a given query. Nevertheless, these efforts focus on developing and optimizing algorithms with different approaches, so there is a real need for a comprehensive survey about the approaches' relative performance, strengths, and pitfalls. Thus here we provide a thorough comparative analysis and experimental evaluation of 13 representative graph-based ANNS algorithms via a new taxonomy and fine-grained pipeline. We compared each algorithm in a uniform test environment on eight real-world datasets and 12 synthetic datasets with varying sizes and characteristics. Our study yields novel discoveries, offerings several useful principles to improve algorithms, thus designing an optimized method that outperforms the state-of-the-art algorithms. This effort also helped us pinpoint algorithms' working portions, along with rule-of-thumb recommendations about promising research directions and suitable algorithms for practitioners in different fields.

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Summary We examine decoupling conditions of domestic extraction of materials, energy use, and sulfur dioxide (SO2) emissions from gross domestic product (GDP) for two BRIC (Brazil, Russia, India and China) countries (i.e., China and Russia) and two Organisation for Economic Co‐operation and Development (OECD) countries (Japan and the United States) during 2000–2007, using a pair of decoupling indicators for resource use (Dr) and waste emissions (De) and the decoupling chart, which can distinguish between absolute decoupling, relative decoupling, and non‐decoupling. We find that (1) during 2000–2007, decoupling between environmental indicators and GDP was higher in the two OECD countries as compared with the two BRIC countries. The key reason is that these countries were in different development stages with different economic growth rates. (2) Changes in environmental policies can significantly influence the degree of decoupling in a country. (3) China, Japan, and the United States were more successful in decoupling SO2 emissions from GDP than in decoupling material and energy use from GDP. The main reason is that, unlike resource use, waste emissions (e.g., SO2 emissions) can be reduced by effective end‐of‐pipe treatment. (4) The decoupling indicator is different from the changing rate of resource use and waste emissions. If two countries have different GDP growth rates, even though they may have similar values using the decoupling indicator, they may show different rates of change for resource use and waste emissions.