While Google Can Understand Known Germany Mobile Number

It also cannot easily interpret the association of attributes without further clarification when those relationships in the Google repository are weakly correlated or non-existent. This clarification is often the result of additional user input.

Of course, Google can learn many of these definitions and relationships over time if enough people search for a set of terms. This is where machine learning (RankBrain) comes in. Instead of refining query sets by the user, the machine makes a better guess based on the user’s perceived intent.

However, even with RankBrain, Google isn’t able to interpret meaning like a human would, and that’s the natural language part of the semantic definition.

So, by definition, Google is NOT a semantic search engine. So what is it?

The transition from “strings” to “objects”

[W]e worked on a smart model — in geek parlance, a “graph” — that understands real-world entities and their relationships to each other: things, not strings.

Official Google Blog

As mentioned, Google is now very good at bringing up Germany Mobile Number specific data. Need a weather report? Traffic conditions? Restaurant review? Google can provide this information without you even having to visit a website, displaying it directly at the top of the search results page. These placements are often based on the Knowledge Graph and are the result of Google’s move from “strings” to “things.”

The move from “Strings” to “Objects” has been great for data-driven searches, especially when it puts those bits of data into the Knowledge Graph. These bits of data are the ones that typically answer the who, what, where, when, why, and how questions of Google’s self-defined “micro-moments.” Google can give users information they didn’t even know they wanted when they wanted it.

However, this push towards entities is not without drawbacks. While Google has excelled at presenting simple, data-driven insights, what it also no longer does is return highly relevant answers for complex query sets.

Here, I’m using “complex queries” to simply mean queries

Germany Mobile Number

that don’t easily match an entity, known data, and/or data attribute – making these queries difficult for Google to “understand”.

Therefore, when you search for a set of complex terms, chances are that you will only get a few relevant results and not necessarily very relevant results. The result is much more a kitchen sink of possibilities than a set of straight answers, but why?

Complex queries and their effect on search

RankBrain uses artificial intelligence to embed large amounts of written language into mathematical entities – called vectors – that the computer can understand. If RankBrain

sees a word or phrase it is unfamiliar with, the machine can guess which words or phrases might have a similar meaning and filter the result accordingly, making it more efficient at handling unfamiliar search queries. . .
Bloomberg Company

 

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