4 ms·
If by "search engine", you mean something similar to Google/Bing then probably not. However, if we expand the concept of "search" to something beyond text on w
by jasode 10y ago
If by "search engine", you mean something similar to Google/Bing then probably not.
However, if we expand the concept of "search" to something beyond text on webpages and "engine" to something beyond a linear algebra pagerank problem that weighs url links, there's room for many more competitors.
Let's say we want to search for "best restaurant":
Method #1 might be searching millions of web pages, twitter posts, newspaper archives, etc where ngram such as "best restaurant" is mentioned. That's what Google/Bing engines already do.
Method #2 might rank restaurants by collecting crowd-sourced opinions. That's what Yelp & Tripadvisor does. (Although Google also piggybacks on their data and lists yelp pages in SRP.)
Method #3 might be a company like Visa/Mastercard analyzing their billions of transactions[1] and based on actual spending amounts & frequency of a billion cardholders, they can also provide their own calculation of a "best restaurant". (I know that Visa/MC already offer limited marketing data to some entities but they don't surface that data to every day web surfers.)
The idea is that there's plenty of room for more imaginative scenarios of #2 & #3. The common theme is that Google doesn't have the data (e.g. credit-card transactions) and therefore, the new "search engines" can give fresh answers that Google algorithms can't provide. To try and boil it down to a simple question: "What interesting answers can a new engine provide that _can't_ be extracted from the text of webpages?"
Btw, I ran across some posts from a Microsoft employee (but not a Bing team member) stating his opinions on building competing search engines. https://news.ycombinator.com/item?id=7011472 https://news.ycombinator.com/item?id=7011472
[1] http://marketrealist.com/2016/10/why-visas-processing-and-international-revenues-have-risen/ http://marketrealist.com/2016/10/why-visas-processing-and-in...
- AznHisoka 10y agoBuzzSumo.com is a good example as well.
- eridius 10y agoMethod #3 would be for calculating popular restaurants, not best restaurants. For example, I bet McDonald's would rate pretty highly with that approach, but it's very nearly as far away as you can get from the idea of a "best restaurant".
- jasode 10y agoPopularity is but one input for "best" -- depending on one's definition of best. There's enough metadata (price, location, cuisine, etc) to correlate with actual payment data to filter out fast food like McDonalds. It doesn't have to be a totally naive statistical approach that gives "dumb" answers. The idea is that what people actually pay for is a different set of vector inputs compared to what people submit reviews for (Yelp/TA) or what people link to (blog with links to favorite city restaurants.) Google's search index is over 100 petabytes but even that gigantic database is missing lots of data that other entities can collect and convert into uncontested search results.