For anyone who works with Microsoft products, there is no doubt that one of the most exciting things is the frequency at which it launches new products. Among the top new offerings on the product line is Azure machine learning.
Thanks to this new addition, AI capabilities are coming to everything else on the Microsoft range of products, including SharePoint. Azure machine learning is a cloud-based offering and it lets users create, deploy and share their advanced analytics.
Understanding how it all works can open up a world of possibilities when it comes to the practical application of the technology in SharePoint.
Why Machine Learning?
Machine learning greatly extends the potential of computers. Computers are complex but they can only do what we tell them to do. They do not have the capability of learning from their mistakes and this is where machine learning comes in.
The concept basically equips computers with what they need to learn from information and become more intelligent with time. How do they do this? They make use of a configured neural network and lots of data.
To illustrate, search engines use the technology to take note of results that get lots of clicks. And the more clicks a result gets, the higher it ranks in later queries. The machine learning model makes use of its neural network to self-train, learn from data and generate outputs.
In the past, this was extremely difficult to set up, but now, thanks to Azure machine learning, it is within reach for Microsoft product users. And more importantly, you do not have to have advanced data science training to make use of it.
If you are a SharePoint user, there are lots of ways you can leverage machine learning to optimize its potential.
Putting Machine Learning to Work in SharePoint
Machine Learning-Based Text Analytics in SharePoint
Among the tools on the Microsoft Azure Machine Learning platform, the Text Analytics API is one of the most useful for SharePoint users. The Text Analytics API is a service based on the cloud which facilitates natural language processing on raw text.
It includes four major functions which are sentiment analysis, keyword extraction, entity recognition and language detection. Essentially, all of these features allow for the extraction of needed information from select content.
For instance, with sentiment analysis, it is possible to learn what customers think of your brand or product through the analysis of text for clues. Keyword extraction, on the other hand, makes it possible to quickly identify the main points in a text.
When you need to recognize and possibly categorize entities in your text, named entity recognition comes in handy. And language detection, as its name suggests, determines the language used to write a text.
In relation to SharePoint, you can integrate this API in a number of contexts. For instance, when saving content, you can use the API to extract keywords and save them to a separate field. Having them on the content page can facilitate information tagging, facilitate the creation of tag clouds and improve the overall search experience.
With a more advanced application, you can analyze the sentiment, tone and quality of text as well. You can also perform content quality assessment, putting an end to inappropriate and poor quality content and identify problems before they blow up.
Though this feature has been available to exclusive users for boatloads of cash, it is now within everyone’s access in the SharePoint environment.
Digital Content Management
Businesses today are creating and storing more digital content than ever before. With the use of machine learning in SharePoint, it is much easier to manage this content and make the most of it. Once again, the potential for this is simply limitless.
One area of application is image tagging. To illustrate, you can upload images and seek suggestions for tags. You can take it even further by using machine learning to relate that image to existing content. With that information, you can give recommended or related content to editors or authors.
You can even use the digital content at hand to mine for sentiments and tags during the creation process. That way, you can be sure of providing a satisfactory experience for all users.
Image tagging using machine learning on SharePoint goes beyond content recognition to extract text from images and also determine where a specific photo was taken.
Other applications of machine learning in SharePoint can help users increase productivity, make better decisions and even enhance security. A good example of this comes to the fore in automated audio content transcription, which makes them significantly more searchable.
Another alluring aspect has to do with file recommendations, which identifies the specific content that you often share with particular contacts to speed things up. Furthermore, when you store content in SharePoint, you can easily reuse things such as charts and graphs as well as paragraphs of your text.
Microsoft’s SharePoint Spaces
One of the most exciting developments made possible through the marriage of SharePoint and machine learning is the emergence of SharePoint Spaces.
In the simplest term, SharePoint Spaces represent Microsoft’s idea of mixed reality in the workplace. SharePoint is an industry leader in collaboration and content services. With mixed reality, it is possible to transform work for everyone using an immersive reality experience.
Users can create visually compelling spaces so as to engage your senses and spark imagination to unlock new potential for collaboration. For instance, if you have new recruits in the office, you can give them a compelling virtual welcome remark allowing them to navigate the premises from their office chair.
It also makes it easier to create personalized, dynamic and relevant content for learning. Product development is also streamlined, with the opportunity to explore prototypes in 3D, visualize improvements and attach annotations.
And the best part about it all is that SharePoint and machine learning empower users to achieve all the above and much more with point and click simplicity. You might want to start with smart templates and gradually work your way up. For example, you can add content that you already have on SharePoint.
The ability to add immersive capabilities to existing content with such simplicity is certainly appealing.
Machine Learning and SharePoint – a Real Game Changer
A majority of SharePoint users are totally reliant on it for their critical day-to-day activities. Whether this has to do with acting as a repository for all their knowledge or running core processes, it plays a central role in more ways than one.
Though advanced automation can add tons of functionality to it, the system still feels rather static. But with machine learning, you can build business solutions that learn from available information as they go. The result is a seamless experience that greatly enhances its potential.
As highlighted above, a combination of SharePoint and machine learning presents limitless possibilities. Think about how you can use the two to streamline operations and ultimately improve the end user’s experience in ways you never thought possible.
Most companies currently have to work very hard to leverage the full potential of SharePoint due to the investment of resources and time this requires. But thanks to this integration, it can foster greater innovation and productivity without asking for too much from your business and tight schedule.
Latest posts by Janica San Juan (see all)
- Machine Learning for Content Filtering – Winning the Battle against Harassment and Trolling - January 30, 2020
- 7 Steps to Correct Data Preparation for Machine Learning - January 22, 2020
- Machine Learning Chatbots: What You Should Know about Neural Conversation Agents - December 18, 2019