The semantic web, also known as Web 3.0, is making

[Shishirgano9]

Its way into the most important traffic distributors on the Internet, such as Google and Facebook. Semantic relationships between topics play an iportant role, especially for Google, in determining the thematic relevance of websites and documents. Below I will explain some approaches to identifying these relationships.



Table of contents [ Hide ]

1 Semantic search: It’s about user context and semantic relationships
2 The different dimensions of semantic relations
3 In what form can entities appear on the network?
4 Social relationships as a ranking factor
5 Semantic Relationships between Websites and Documents
6 How does Google identify semantic relationships between topics?
6.1 Search behavior
6.2 Surfing behavior
6.3 Internal linking of Wikipedia
7 Additional tools for semantic relationship analysis
7.1 Vionto / Eyeplorer
7.2 Vocabulary Uni Leipzig
7.3 Semager
Semantic search: It's about user context and semantic relationships
In particular, the new Google algorithm and the increasingly present Knowledge Graph are all about user context and semantic relationships between terms and entities within ontologies. (see also Semantic Optimization at Google: From Entity to Brand )

entities within an ontology
entities within an ontology



The different dimensions of semantic relations
Semantics is all about nodes and edges or relationships between entities, as described by Svenja Hintz in Semantic Search: Google now pays attention to inner values . The semantic relationships can be divided into the following levels:

search intent
user context by time, location, device and search sequence
Thematic relevance of domains and documents within the ontology
Content depth / holistics of domains and documents
semantic search levels
Levels of Semantic Search



I have already discussed the search intent of keywords and their gambling data romania identification in detail in the article The purpose of the landing page follows the search intent: How do you identify the search intent of keywords? I will not go into the user context in relation to device, location and search sequence here. Karl Kratz has already written enough about the depth of content, holistic approach and holism in terms of good content and WDF*IDF. I am not a fan of rehashing content that has already been discussed enough. That is why I will stick with the references to Karl at this point.

I would like to go into more detail on the topic of thematic relevance within ontologies. To start with, here is an introduction to the topic of ontologies and the digital entities they may contain.