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.
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?
For example, this is how I would design the system:
User’s input: “Where do you go to get your eyes tested?”
System output: “Opticians. Certainty: 95%”
This would be calculated as follows:
- The input is parsed from natural language into a simple search string, probably something like “eye testing” in this case. The term “Where do you go” would also be interpreted by the system and used when comparing results.
- The search string would be fed into a search engine.
- The system would then compare the contents of the results to find matching words or phrases taking note of what the question is asking (i.e. what, where, who, how etc.)
- Once a suitable answer is determined, the system displays it to the user along with a measure of how sure it is that the answer is correct.
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.
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.
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.
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
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.
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.
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.
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.
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:
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).
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".
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.
See also the related question on open source QA frameworks.
Update: