Why a ‘Research’ Engine is better than Search.
Why would you want to use a Research Engine over a Search Engine? The answer is simple: You want a more in-depth answer than a search engine could ever provide. When we first started showing our platform to the world, the first thing we heard was: “Oh, okay, so you’re a search engine.”
Well, no, not really. It is to be expected that people will try and fit things into their Worldview, as we’ve mentioned previously. Thus while it’s a predictable reaction, it’s also frustrating because once so pigeon-holed, it is difficult to have the concept re-assigned.
So before we go any further: We are NOT a Search Engine. We ARE a Research Engine.
The differences? Well, when you use a Search Engine you get thousands of results with varying degrees of relevancy, requiring your own time to sort through and determine if you’ve found what you’ve been looking for. Results are pulled from a local or networked data store, derived specifically from that engine’s crawling activities. While there is Machine Learning going on under the hood, to be sure, the expectations of a near-immediate response predicate that the learning undertaken be completed quickly, so that the response may be sent to the user. Further, a Search Engine tends to compartmentalize your query, so that there is a diminishing return to the number of query terms you can enter, and how that will affect the relevancy of your results. In the context of a Research Engine, the more query terms you enter, the better! We don’t (entirely) compartmentalize your query terms. We consider the query as a whole, breaking it into parts for certain algorithms, but considering the end result as a whole rather than a loosely-associated series of parts.
Another distinction between the Research Engine and widely-known Search Engine is the idea of immediate gratification. One of the core requirements of a search engine is speed. This requirement arguably outranks relevancy. If your response is slow, the users will go. This is the age-old internet adage. So how do we get around this? Is it really a good thing that a response be fast? What if a response took a bit more time, but delivered rich, highly-relevant results? Would this not ultimately save time and resources?
Our conclusion: It absolutely would save time and resources.
So our response to “fast” is: “Hey, go take a walk, or have a beer or some such. Go enjoy life. We’ll be in touch with you shortly.” It really all depends on the question you’re asking. We’ll look at the amount of research required, and either respond immediately, or respond with a “we’re working on it, get back with you shortly” message.
And, indeed, within a short time, you’ll get an email, a text message or a phone call from HAIDIE, telling you she has some information for you to look at. Thus the nature of this beast is very different from that of a typical Search Engine. On our platform, the conversation is on going, as the platform desires to learn from the user, and to maintain a conversation with the user, rather than the arcane concept of learning the machine and issuing a limited set of finite commands. The world is constantly changing. Information expands daily. If you want to maintain an in-depth understanding, you don’t want to search, you want to research.