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百度搜索算法大盘点2013-2019-2.用户需求满足

用户需求满足是百度搜索算法中一个非常重要的因素，尤其是在近年来的更新中更加突出。在2013年至2019年期间，百度搜索算法经历了多次重大更新，其中涉及到的用户需求满足方面有以下几个方面： 1. 增加本地搜索功能：2013年百度推出了“百度糯米”服务，着重增强了对本地商家和服务的搜索结果展示。2014年，百度还推出了“百度地图开放平台”，方便开发者将本地信息加入到搜索结果中，满足用户对本地信息的需求。 2. 改进移动搜索适配：2015年，百度推出了“移动优先索引”算法，提高了移动设备上的搜索体验。2018年，推出了“智能小程序”，方便用户在手机端进行搜索和交互。 3. 精准化搜索结果：2017年，百度推出了“RACE”（Ranking Algorithm for Customer Evaluation），优化搜索结果的质量并满足用户个性化需求。 4. 加强搜索词意理解能力：2018年，百度推出了“零距离”计划，升级搜索技术，通过理解搜索用户的意图，为用户提供更精准的搜索结果。总之，用户需求满足是百度搜索算法中一个非常重要的方面，而百度在近年来的算法更新中，不断强化了对用户需求的关注和满足，使得搜索结果更加精准、贴心。

Public @ 2023-06-27 04:50:24

关于百度上线 “闪电算法”的公告

2017年10月初，“闪电算法”上线，移动搜索页面首屏加载时间将影响搜索排名。移动网页首屏在2秒之内完成打开的，在移动搜索下将获得提升页面评价优待，获得流量倾斜；同时，在移动搜索页面首屏加载非常慢（3秒及以上）的网页将会被打压。广大站长优化页面首屏加载时间，优化的技术建议包括但不限于:资源加载：1、将同类型资源在服务器端压缩合并，减少网络请求次数和资源体积。2、引用通用资源，充分利用浏览器缓存。3

Public @ 2018-06-23 15:21:53

百度搜索持续与有损用户体验的落地页广告作战

近年来，百度搜索遭到不少用户投诉，其中最常见的问题是一些有损用户体验的落地页广告。这些落地页广告往往通过虚假标题和描述吸引用户点击，却将用户带到与描述不符的页面上，甚至存在恶意软件和诈骗链接，给用户带来极大的困扰和风险。面对这样的问题，百度搜索多次发布声明承诺加强广告审核和打击违规广告。然而实际效果并不明显，很多仍然存在问题的广告仍然可以在搜索结果页面上出现。为此，许多消费者纷纷表示对百度搜索

Public @ 2023-04-13 15:00:54

百度搜索算法大盘点2013-2019-5.落地页体验问题

5.落地页体验问题5.1 冰桶算法5.0一直以来，百度搜索致力于提升搜索用户的浏览体验，营造健康的搜索生态。2014年8月22日，百度搜索针对低质页面问题发布冰桶算法，经过不断更新迭代，在2018年11月对冰桶算法进行升级，上线冰桶算法5.0。冰桶算法5.0以《百度移动搜索落地页体验白皮书4.0》为标准，对落地页广告、APP调起、展开全文功能等问题进行控制。《百度移动搜索落地页体验白皮书4.0》—

Public @ 2012-05-29 15:21:24

百度搜索算法大盘点2013-2019

最新更新章节：2019-06-13为了给搜索用户提供更加优质便捷的搜索体验，百度搜索始终不忘初心，致力与内容生产者、资源提供者携手共建和谐健康的搜索生态。 2013年，百度搜索发布首篇算法公告。经过6年的发展沉淀，百度搜索共计发布了13个算法、48篇公告及算法解读文章。 2019年，为帮助广大站长快速系统地了解搜索算法及规则、更好地提升自身网站质量，我们将算法进行梳理分类，汇编为《百度搜索算法大盘

Public @ 2021-07-31 15:21:27

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[ DB ] CONNECT:[ UseTime:0.023901s ] mysql:dbname=briline.net;host=106.14.77.182;port=3306;charset=utf8
[ SQL ] SHOW COLUMNS FROM `ob_article` [ RunTime:0.017052s ]
[ SQL ] SELECT * FROM `ob_article` WHERE `id` = 9489 LIMIT 1 [ RunTime:0.016233s ]
[ EXPLAIN : array ( 'id' => 1, 'select_type' => 'SIMPLE', 'table' => 'ob_article', 'type' => 'const', 'possible_keys' => 'PRIMARY', 'key' => 'PRIMARY', 'key_len' => '4', 'ref' => 'const', 'rows' => 1, 'extra' => NULL, ) ]
[ SQL ] select * from `ob_article_tongji` where category_id=12 and mark_type='cate' order by times desc limit 15 [ RunTime:0.016306s ]
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[ SQL ] select * from `ob_article_tongji` where category_id=12 and mark_type='tags' order by times desc limit 100 [ RunTime:0.016382s ]
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[ SQL ] select * from `ob_article_tongji` where category_id=12 and mark_type='tags' order by rand() limit 30 [ RunTime:0.016781s ]
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[ SQL ] SELECT * FROM `ob_article` WHERE `id` = 9489 LIMIT 1 [ RunTime:0.016140s ]
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[ SQL ] update `ob_article` set views=views+1 where id=9489 [ RunTime:0.016918s ]
[ SQL ] SELECT COUNT(*) AS tp_count FROM `ob_article` WHERE `category_id` = 12 AND `cate` = '威海百度搜索引擎算法' AND `status` <> -1 LIMIT 1 [ RunTime:0.023376s ]
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[ SQL ] SELECT COUNT(*) AS tp_count FROM `ob_article` WHERE `category_id` = 12 AND `tags` = '威海百度搜索算法大盘点2013-2019' AND `status` <> -1 LIMIT 1 [ RunTime:0.023804s ]
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