Google uses Natural Language Processing (NLP) routines to convert its understanding of text into topics and concepts (Entities). We looked out how much understanding Google misses using this approach in the Software sector.
InLinks analyzed the page content of the top 10 Google results (in the US Market) ranking for the phrase Native Trends and compared the Named Entities recognized by Google’s NLP API with the proprietory routines designed by Inlinks to uncover gaps in Google’s machine learning in the Software sector
The results showed that 24.8% of entities seen on the results in the Software sector SERPS (search engine Results pages) were positively identified by Google.
This compares to 18.5% average across all analyzed industry sectors.
Different sectors tend to be analyzed with a different degree of accuracy by the search engines. This stems from two main challenges.
|Software Industry||Google Analysis||InLinks Analysis|
|Avg. Number of words per page||883|
|Avg. Number of Topics per page||11.4||46|
|Benchmark - Avg. nb of entities/page (all sectors)||8.6||47.2|
|Of which, Topic types are:|
|- Cities & geo. areas||11||9|
Google’s Search API returned URLs for the following sites competing for this phrase:
#offers.nativeadvertisinginstitute, #pubmed.ncbi.nlm.nih.gov, #thefoundry.nyc, #alibabacloud, #facebook, #forbes, #redhat, #techrepublic
The texts of each page are then sent to Google’s NLP API, in order to determine which entities are identified by the search engine. These are important for search since Google is then able to link these to its Knowledge Graph to feed its services including Google Discover, Google search, Voice Search and Google News. (Although, correct identification does not guarantee inclusion in these results)
Here is first of all the synthesis of the results returned by Google:
Here are some errors in the categorization of entities:
By understanding where Google is failing to recognize important concepts within the industry, there is an opportunity for companies in the sector to write clearer content that Google can better understand.
Another option is to explicitly state these concepts in Webpage schema for machine learning algorithms to take into account. This would require using Schema.org/WebPage and the "about" and mentions" properties for important concepts such as Software development, Software, Server (computing).
Internal linking of topics topages dedicated to each important topic will also help to reduce cannibalisation of content in Google’s understanding of contect within your content.
Google's understanding of the Software market, based on its NLP algorithms remains limited at 24.8% for this industry. Businesses either need to improve their schema or make their content more understandable by Google to improve its level of understanding.
Kubernetes, Google, BigQuery, SUSE, Cloud computing, Hyperscale computing, Microsoft, Machine learning, Google Cloud Platform, Red Hat, International Institute of Information Technology, Hyderabad, Amazon Web Services, Microsoft SQL Server, OpenShift, Amazon (company), Apple Inc., VMware, Industrial internet of things, Cisco Systems, Veeam, New Relic, Pure Storage, Intel, Microsoft Most Valuable Professional, Internet of things, Google Developer Expert, Big data, DevOps, Git, AWS Lambda
Facebook, Arizona, Bullhead City, Arizona, Native Americans in the United States, Apache, Navajo, Opata, U.S. Route 95
Kubernetes, Cloud computing, Machine learning, Europe, North America, Asia, DevOps, Docker (software), Amazon Web Services, Apple Inc., AWS Lambda, Consul (software), Amazon Elastic Compute Cloud, Content as a service, Nginx, Prometheus (software)
Alibaba Group, Cloud computing, Cloud native computing, Yang Haoran, Luzhi, Yuquan Shenxiu, Microsoft, Kubernetes, China, Docker (software)
Meredith Corporation, All rights reserved
Amazon Web Services, Forrester Research, Cloud computing, Microsoft Azure, Alibaba Cloud, TechRepublic, Multicloud, ZDNet, Moderna, Lowe's, Etsy, Network security, Kubernetes, Pandemic, Microsoft
United States, PubMed, Infective endocarditis, West Virginia, Morgantown, West Virginia, West Virginia University, Aortic valve replacement, California, Mayo Clinic, La Jolla, University of California, San Diego, Analysis of covariance, Generalized linear model, Chi-squared test, Ampere hour, China
Kubernetes, Ovum Ltd., DevOps, Linux
Alaska, PubMed, Public health, Alaska Natives, Anchorage, Alaska, United States, National Cancer Institute, Li Xuerui
World Association of Newspapers and News Publishers, Native advertising, T Brand Studio, JP/Politikens Hus, Mediahuis Nederland