Wolfram Alpha’s: Features, Workings, Uses and Technology

Posted on 28 August, 2009 | No Comments

Between Google’s generosity on one end and Wolfram Alpha’s terseness on the other, a growing spectrum of search engine approaches is emerging, with the aim of making it easier for users to find what they want on the web.

Microsoft offered its updated search engine, named Bing. In Bing, Microsoft seems to have gotten over the number of results (that is, links) as the sole parameter of search quality. Instead, the focus is on increasing the utility of a relatively smaller number of search results.

Bing does this by offering related search terms and search history on the left pane, as well as a quick view panel on the right for a sneak look at the link page without visiting it.

Wolfram Alpha, the computational knowledge engine, is set for a major boost with news that some of its content is to feature within Microsoft’s Bing search engine.

In a nutshell, Wolfram and his team have built what he calls a “computational knowledge engine” for the Web. OK, so what does that really mean? Basically it means that you can ask it factual questions and it computes answers for you.

It doesn’t simply return documents that (might) contain the answers, like Google does, and it isn’t just a giant database of knowledge, like the Wikipedia. It doesn’t simply parse natural language and then use that to retrieve documents, like Powerset, for example.

Instead, Wolfram Alpha actually computes the answers to a wide range of questions — like questions that have factual answers such as “What country is Timbuktu in?” or “How many protons are in a hydrogen atom?” or “What is the average rainfall in Seattle?”

Think about that for a minute. It computes the answers. Wolfram Alpha doesn’t simply contain huge amounts of manually entered pairs of questions and answers, nor does it search for answers in a database of facts. Instead, it understands and then computes answers to certain kinds of questions.

How Does it Work?

Wolfram Alpha is a system for computing the answers to questions. To accomplish this it uses built-in models of fields of knowledge, complete with data and algorithms that represent real-world knowledge.

For example, it contains formal models of much of what we know about science — massive amounts of data about various physical laws and properties, as well as data about the physical world.

Based on this you can ask it scientific questions and it can compute the answers for you. Even if it has not been programmed explicity to answer each question you might ask it.

But science is just one of the domains it knows about — it also knows about technology, geography, weather, cooking, business, travel, people, music, and more.

It also has a natural language interface for asking it questions. This interface allows you to ask questions in plain language, or even in various forms of abbreviated notation, and then provides detailed answers.

The vision seems to be to create a system wich can do for formal knowledge (all the formally definable systems, heuristics, algorithms, rules, methods, theorems, and facts in the world) what search engines have done for informal knowledge (all the text and documents in various forms of media).

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