Google’s Knowledge Graph Search API & SEO: A Comprehensive Guide

Google’s Knowledge Graph Search API & SEO: A Comprehensive Guide

Google introduced the Knowledge Graph to help searchers discover new information quickly. Users can search for places, people, companies, and products, finding instant results that are most relevant to the query. Knowledge Graph is a collection of topics connecting to other entities. Google uses Knowledge Graph to provide a better search experience for users, as it can better understand different topics and their relationships to each other.

Knowledge Graph API

A knowledge graph API is a programming interface enabling developers to interact with a knowledge graph, which is a structured database representing information as interconnected entities and their relationships. It provides methods to query, update, and manage data stored in the graph format, where nodes represent entities and edges define relationships between them. For instance, a knowledge graph might store data such as “Marie Curie>discovered>Radium,” linking entities through semantic relationships. APIs for knowledge graphs enable applications to retrieve specific subsets of this data or add new connections without needing direct access to the underlying database.

Using Python To Call The API

There are four different clients that Google enables the API to be called via: Python, Java, JavaScript, and PHP. An example starting point for each can be found on the relevant page in the documentation. For this example, use Python as it is the language that is most familiar with.

Creating an API Key is the first step. For generating an API key, go to the Google API console and navigate to the credentials page. Then go to the API library, search for Knowledge Graph, and then enable it. You can save a note of your API key, and be able to easily find the API key again by clicking on the API that has already generated.

A Simple API Request. To retrieve entities matching a query, together with the results score for each entity, there is a simple piece of Python code that can run, either in Google Colab or in your local environment. Producing an outcome involves setting a couple of parameters that are needed. The first thing that is needed to add is the API key, followed by the query for which you would like to generate the results. The parameters are then set to call the API key already added and query selected, enabling you to easily change the query that is searched while running the code. Further, other parameters included are Languages and Types.

Extracting Even More. Returning the entities and their result score, and there is so much more that can be received from the Knowledge Graph API. With a few more lines of code and a few functions, we can produce a JSON object with all the answer fields stored for each entity. Initially, it is requested to return the page from the session that would be searched via the API. Then, use a similar API request as in the original code, enabling calling it in conjunction with our query request using the same parameters. Then, enter the API key to return a response object with the full data. To see the results a little easier and help make more sense of the response, enable normalizing the JSON object into a Pandas DataFrame, which would take each field and transfer it into a column, with each entity a different row.

Response Fields. Several fields would be extracted for each entity within the Knowledge Graph API: id, name, type, description, image, detailed Description, url, and resultScore.

Confidence Score. resultScore representing Google’s confidence in its understanding of the entity, essentially the perceived strength of the relationship between the entity that Google has recognized for the query, and the entity that has been returned. The higher the result score, the more confidence Google has in the entity being the best match for the query.

Extracting Insights

Keyword Research. Completing keyword research is worth considering whether the current targeting makes sense for a strong entity that exists for a particular keyword. Google’s overarching goal is to provide the most useful information in search results.

Brand Building includes the use of entities for building a brand or a company’s organic search presence and authority in a particular space. It is useful to know the entities behind a certain query, giving insights into the search insights for keywords and making it even easier to create authoritative, helpful content in line with this.

Competitor Research. API provides a ranked list of entities appearing for queries, and you can view a high level of insights rather than performing numerous searches to see what appears. This would enable you to review competitors’ performance for particular queries and how you compare. You can also use these insights to make sure that you can increase your confidence score for overtaking competitors in the results. The API allows you to keep track of this regularly and report on any changes you see, potentially before any SERP feature change