Introducing the Knowledge Graph: things, not strings【阅读翻译】
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Search is a lot about discovery—the basic human need to learn and broaden your horizons.?But searching still requires a lot of hard work by you, the user. So today I’m really excited to launch the Knowledge Graph, which will?help you discover new information quickly and easily.
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搜索更多的和发现相关-学习基本的用户需求和扩展眼界。但是，搜索仍然要求你来做一些比较困难的工作，所以，现在我非常高兴能够从事知识图谱，一个可以帮助你快速和简单发现信息的技术。
Take a query like [taj mahal]. For more than four decades, search has essentially been about matching keywords to queries. To a search engine the words [taj mahal] have been just that—two words.
以query[taj mahal].为例，在过去的四十年中，搜索的本质是匹配query的关键词，对于搜索引擎，输入的query[taj mahal].被认为是两个单词。
But we all know that [taj mahal] has a much richer meaning. You might think of one of the world’s most beautiful monuments, or a Grammy Award-winning musician, or possibly even a casino in Atlantic City, NJ. Or, depending on when you last ate, the nearest Indian restaurant. It’s why we’ve been working on an intelligent model—in geek-speak, a “graph”—that understands real-world entities and their relationships to one another: things, not strings.
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但是我们都知道[taj mahal]这个query有丰富的含义。你可以认为它表示世界上最壮美的纪念碑，或者格莱美奖的获奖音乐家，又或者是新泽西区近大西洋城市的一个俱乐，又或者是离你最近的印第安餐厅。这就是为什么我们需要开发一个新的模型，图谱-可以理解真实世界的实体和实体之间的关联：实体而不是字符串。
The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query.?This is a critical first step towards building the next generation of search, which taps into the collective intelligence（集体智慧） of the web and understands the world a bit more like people do.
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知识图谱可以使你搜索任何谷歌索引的事物、人和地方，比如：标志性性建筑、名人、城市、球队、建筑、地理特征、电影、神灵和艺术品等，并迅速获得和检索query的关联信息。这是迈向下一代搜索引擎的重要一步，走向互联网的集体智慧，像人类一样理解世界。
Google’s Knowledge Graph isn’t just rooted in public sources such as?Freebase, Wikipedia and the CIA World Factbook. It’s also augmented at a much larger scale—because we’re focused on comprehensive breadth and depth.?It currently contains more than 500 million objects, as well as more than 3.5 billion facts about and relationships between these different objects.?And it’s tuned based on what people search for, and what we find out on the web.
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谷歌的知识图谱不只是针对公共的数据资源，比如Freebase、维基百科和CIA世界概况，他面向的是一个大的范围，因为我们面对的是理解的广度和深度。当前谷歌已经收录了5亿多对象实体，350亿实体之间的关联信息。谷歌转向基于用户在检索什么和用户在互联网上获得了什么。
The Knowledge Graph enhances Google Search in three main ways to start:
知识图谱提高了谷歌的检索，主要通过一下几个方法：
1. Find the right thing
Language can be ambiguous—do you mean Taj Mahal the monument, or Taj Mahal the musician??Now Google understands the difference, and can narrow your search results just to the one you mean—just click on one of the links to see that particular slice of results:
1.查找正确的事物
语言可以是模糊的，比如，你要检索的泰姬陵是一个遗迹还是一个音乐家？现在谷歌可以理解出不同，并且将所有可能的结果归纳分组，你只需要点击其中一个连接去查看针对特定含义的所有结果。
This is one way the Knowledge Graph makes Google Search more intelligent—your results are more relevant because we understand these entities, and the nuances in their meaning, the way you do.
这是谷歌让检索更加智能的一种方法，因为谷歌像用户一样，理解实体和实体含义间的细微差别。
2. Get the best summary
With the Knowledge Graph, Google can better understand your query, so we can summarize relevant content around that topic, including key facts you’re likely to need for that particular thing. For example, if you’re looking for Marie Curie, you’ll see when she was born and died, but you’ll also get details on her education and scientific discoveries:
2.获得最优的结构化摘要
使用知识图谱，谷歌可以更好的理解query，所以我们可以概括主题的相关内容，相关的结构化字段描述。例如，如果你检索居里夫人，你可以看到她的出生和死亡时间，同时，你也可以看到她教育和科学发现的详细信息。
How do we know which facts are most likely to be needed for each item? For that, we go back to our users and study in aggregate what they’ve been asking Google about each item.?For example, people are interested in knowing what books Charles Dickens wrote, whereas they’re less interested in what books Frank Lloyd Wright wrote, and more in what buildings he designed.
我们怎么得知每个实体需要展现哪些属性？对此我们回归用户，对用户在谷歌检索的实体属性进行聚合。比如，人们对查尔斯.狄更斯的作品感兴趣，但是人们对Frank Lloyd Wright写的作品不感兴趣，但是对他设计的建筑感兴趣。
The Knowledge Graph also helps us understand the relationships between things. Marie Curie is a person in the Knowledge Graph, and she had two children, one of whom also won a Nobel Prize, as well as a husband, Pierre Curie, who claimed a third Nobel Prize for the family. All of these are linked in our graph. It’s not just a catalog of objects; it also models all these inter-relationships. It’s the intelligence?between?these different entities that’s the key.
只是图谱可以帮助我们理解事物之间的关联。比如Marie Curie是知识图谱中的一个人，她有两个孩子，其中一个和他丈夫一样获得了诺贝尔奖，成为家中第三个获得诺贝尔奖的人。在我们图谱中这些关系是链接在一起的，不只是对象的一个分类，而是这些内部关联的模型，这些不同实体之间的信息是关键。
3. Go deeper and broader
Finally, the part that’s the most fun of all—the Knowledge Graph can help you make some unexpected discoveries. You might learn a new fact or new connection that prompts a whole new line of inquiry. Do you know where Matt Groening, the creator of the Simpsons (one of my all-time favorite shows), got the idea for Homer, Marge and Lisa’s names? It’s a bit of a surprise:
3.向深度和广度迈进
最后，这部分是最有趣的，知识图谱可以带给你一些意想不到的发现。你可能发现新的事实或者新的关系导致一项新的调研。你知道?Matt Groening的名字是怎么来的么，Simpsons?的创造者通过Homer, Marge and Lisa这三个名字得到得灵感，这是一个惊喜吧。
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We’ve always believed that the perfect search engine should understand exactly what you mean and give you back exactly what you want. And we can now sometimes help answer your next question before you’ve asked it, because the facts we show are informed by what other people have searched for. For example, the information we show for Tom Cruise answers 37 percent of next queries that people ask about him. In fact, some of the most serendipitous discoveries I’ve made using the Knowledge Graph are through the magical “People also search for” feature. One of my favorite books is?The White Tiger, the debut novel by Aravind Adiga, which won the prestigious Man Booker Prize. Using the Knowledge Graph, I discovered three other books that had won the same prize and one that won the Pulitzer. I can tell you, this suggestion was spot on!
我们已经相信优秀的搜索引擎应该能够准确理解你要表达的含义，并且把你想检索的准确的返回回来。并且我们可以在你问下一个问题之前回答你想问的问题，因为我们通过其它用户的搜索记录来推理你下一步的检索。比如，对于汤姆克鲁斯的检索结果中，我们能够回顾37%的下一个检索。事实上，很多通过知识图谱的不可思议的发现是通过“用户也检索了”来获得。我非常喜欢的一本书《White Tiger》，Aravind Adiga的第一部小说，获得了著名的布克奖。通过知识图谱，我发现他的其它三本书也获得了布克奖，还有一本获得了普利策奖。我可以告诉你，这个推荐被发现了。
We’ve begun to gradually roll out this view of the Knowledge Graph to U.S. English users. It’s also going to be available on smartphones and tablets—read more about how we’ve?tailored this to mobile devices. And watch our video (also available on our?site?about the Knowledge Graph) that gives a deeper dive into the details and technology, in the words of people who've worked on this project.
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We hope this added intelligence?will give you a more complete picture of your interest, provide smarter search results, and pique your curiosity on new topics.?We’re proud of our first baby step—the Knowledge Graph—which will enable us to make search more intelligent, moving us closer to the "Star Trek computer（星际迷航计算机）" that I've always dreamt of building. Enjoy your lifelong journey of discovery, made easier by Google Search, so you can spend less time searching and more time doing what you love.
我们可以逐步的将知识图谱的这一观点发布给英文用户，并且将适用于智能手机和平板电脑。我们的视频已经发展到一个更深入的细节和技术。
我们希望添加智能搜索后，可以提供给你一个关于你兴趣的较为完整的图谱，提供轻量级的搜索结果，同时激发你对新主题的兴趣。对于我们迈出的知识图谱的第一步我们很骄傲，这可以使我们的检索更加智能，使我们更加靠近 星际迷航计算机。享受你毕生的探索之旅，谷歌搜索引擎将帮助你简单的开启探索过程，你可以花费较少的时间来搜索同时使用更多的时间来做你喜欢的事情。
Posted by Amit Singhal, SVP, Engineering
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When you search on Google for a person, place, or thing, you might see a section to the right of your search results that highlights facts, photos, and other snippets of information about your search. Use this section to find quick information and facts about the subject or to start exploring related subjects.
To give it a try, search for your favorite movie, landmark, historical figure, or try one of these:?See these quick facts on on the go too!?Information about people, places, or things can also been seen on Google from your tablet and smart phone devices.
The information shown in this section comes from what we call the?Knowledge Graph, a massive collection of information about real-world things and their connections to other things. The graph gathers information about a person, place, or thing from many sources, then refines the resulting information based on the most popular questions people ask about that subject.
Here are just some of the sources for this web of information:
The information in these sections is compiled by automated systems, so there's always a chance that some of the information is incorrect or no longer relevant. If you see any issues, just click the "Report a problem" link at the bottom of the box and identify the piece of content in question.
We'll incorporate your feedback to help improve the content in the future. In the meantime, know that the information you see changes naturally over time just as search results do.
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