有没有可以直接给出答案的搜索引擎? [英] Is there a search engine that will give a direct answer?
问题描述
我一直在想这个问题，我不知道为什么Google还没有尝试过-也许他们已经尝试了，但我只是不知道.
I've been wondering about this for a while and I can't see why Google haven't tried it yet - or maybe they have and I just don't know about it.
是否有一个搜索引擎，您可以输入一个问题，该问题将为您提供单个答案，而不是结果列表，您必须仔细搜索才能找到想要的知识?
Is there a search engine that you can type a question into which will give you a single answer rather than a list of results which you then have to trawl through yourself to find what you want to know?
例如，这就是我设计系统的方式:
For example, this is how I would design the system:
用户输入:您要去哪里进行眼睛测试?"
User’s input: "Where do you go to get your eyes tested?"
系统输出:配镜师.确定性:95％"
System output: "Opticians. Certainty: 95%"
这将计算如下:
- 将输入内容从自然语言解析为简单的搜索字符串，在这种情况下，可能类似于眼力测试".系统还会解释并在比较结果时使用去哪里"一词.
- 搜索字符串将被输入到搜索引擎中.
- 然后，系统将比较结果的内容，以找到匹配的单词或短语，同时注意问题的所在(即什么，在哪里，在谁，如何等)
- 确定合适的答案后，系统会向用户显示该答案以及确定答案正确与否的度量.
由于Internet的分散性，正确答案可能会多次出现，尤其是对于简单的问题.对于这个特定的示例，系统可以很容易地识别出这个词在结果中不断涌现，并且几乎可以肯定地是在寻找答案.
Due to the dispersed nature of the Internet, a correct answer is likely to appear multiple times, especially for simple questions. For this particular example, it wouldn’t be too hard for the system to recognise that this word keeps cropping up in the results and that it is almost certainly the answer being searched for.
对于更复杂的问题，将显示较低的确定性，并且可能有多个具有不同确定性级别的结果.还可以为用户提供查看系统计算结果的来源的机会.
For more complicated questions, a lower certainty would be shown, and possibly multiple results with different levels of certainty. The user would also be offered the chance to see the sources which the system calculated the results from.
此系统的要点是它简化了搜索.很多时候，当我们使用搜索引擎时，我们只是在寻找真正简单或琐碎的东西.返回一长串结果似乎不是回答问题的最有效方法，尽管几乎可以肯定地将答案隐藏在这些结果中.
The point of this system is that it simplifies searching. Many times when we use a search engine, we’re just looking for something really simple or trivial. Returning a long list of results doesn’t seem like the most efficient way of answering the question, even though the answer is almost certainly hidden away in those results.
只需查看上述问题的Google搜索结果，就可以看出我的观点:
Just take a look at the Google results for the above question to see my point: http://www.google.co.uk/webhp?sourceid=chrome-instant&ie=UTF-8&ion=1&nord=1#sclient=psy&hl=en&safe=off&nord=1&site=webhp&source=hp&q=Where%20do%20you%20go%20to%20get%20your%20eyes%20tested%3F&aq=&aqi=&aql=&oq=&pbx=1&fp=72566eb257565894&fp=72566eb257565894&ion=1
给出的结果不能立即回答问题-用户必须先搜索它们，然后才能找到他们真正想要的答案.搜索引擎是很棒的目录.它们确实可以为您提供有关某个主题的更多信息，或者告诉您在哪里可以找到服务，但是它们并不能很好地回答直接问题.
The results given don't immediately answer the question - they need to be searched through by the user before the answer they really want is found. Search engines are great directories. They're really good for giving you more information about a subject, or telling you where to find a service, but they're not so good at answering direct questions.
在创建系统时，必须考虑很多方面，例如，在计算结果时必须考虑网站的准确性.
There are many aspects that would have to be considered when creating the system – for example a website’s accuracy would have to be taken into account when calculating results.
尽管该系统可以很好地解决简单的问题，但要使其适用于更复杂的问题可能是一项艰巨的任务.例如，需要将常见的误解作为特例处理.如果系统发现证据表明用户的问题具有常见的误解作为答案，则应在提供答案时指出这一点，或者甚至不理会最常见的答案，而赞成由网站提供的答案是一个普遍的误解.所有这些都必须通过比较冲突源的准确性和质量来权衡.
Although the system should work well for simple questions, it may be quite a task to make it work for more complicated ones. For example, common misconceptions would need to be handled as a special case. If the system finds evidence that the user’s question has a common misconception as an answer, it should either point this out when providing the answer, or even simply disregard the most common answer in favour of the one provided by the website that points out that it is a common misconception. This would all have to be weighed up by comparing the accuracy and quality of conflicting sources.
这是一个有趣的问题，需要进行大量研究，但是值得花时间和精力吗?并非总是正确的，但是它将使用户进行简单查询的速度大大提高.
It's an interesting question and would involve a lot of research, but surely it would be worth the time and effort? It wouldn't always be right, but it would make simple queries a lot quicker for the user.
推荐答案
这种系统称为自动问题解答(QA)系统或自然语言搜索引擎.请勿将其与由人产生答案的社交问题解答服务相混淆.质量检查是一个研究充分的领域，近十年来 TREC 质量检查领域的出版物就证明了这一点，但这是一个自然语言处理(NLP)领域中比较困难的任务智能范围(解析，搜索，信息提取，共指，推断).这可以解释为什么今天的免费在线系统相对较少，而大多数系统更像是演示.其中包括:
Such a system is called an automatic Question Answering (QA) system, or a Natural Language search engine. It is not to be confused with a social Question Answering service, where answers are produced by humans. QA is a well studied area, as evidenced by almost a decade of TREC QA track publications, but it is one of the more difficult tasks in the field of natural language processing (NLP) because it requires a wide range of intelligence (parsing, search, information extraction, coreference, inference). This may explain why there are relatively few freely available online systems today, most of which are more like demos. Several include:
- AnswerBus
- START - MIT
- QuALiM - Microsoft
- TextMap - ISI
- askEd!
- Wolfram Alpha
主要搜索引擎已经对问答技术表现出兴趣.埃里克·史密特(Eric Scmidt)在2011年6月1日的一次采访中说，谷歌的新搜索策略是提供答案，而不仅仅是链接. 我们可以从字面上计算出正确的答案，"施密特说，它引用了人工智能技术的进步."(
Major search engines have shown interest in question answering technology. In an interview on Jun 1, 2011, Eric Scmidt said, Google’s new strategy for search is to provide answers, not just links. "'We can literally compute the right answer,' said Schmidt, referencing advances in artificial intelligence technology" (source).
Google Enterprise产品负责人Matthew Goltzbach 表示问题解答是企业搜索的未来."雅虎还预测，搜索的未来将涉及用户真实及时解答而不是链接.如.
Matthew Goltzbach, head of products for Google Enterprise has stated that "Question answering is the future of enterprise search." Yahoo has also forecasted that the future of search involves users getting real-time answers instead of links. These big players are incrementally introducing QA technology as a supplement to other kinds of search results, as seen in Google's "short answers".
尽管IBM扮演Jeopardy角色的Watson为普及回答问题的机器做了很多工作，但许多
While IBM's Jeopardy-playing Watson has done much to popularize machines answering question (or answers), many real-world challenges remain in the general form of question answering.
另请参阅开源质量检查框架上的相关问题.
See also the related question on open source QA frameworks.
更新:
- 2013/03/14:Google和Bing搜索主管讨论搜索如何演变为会话式问答( 查看全文
