The evolution of the Artificial Intelligence has undergone phases of topsy-turvies. In its early stages, AI failed to prove its viability in reshaping the world. The so called phase of disappointment was known as AI Winter. In the present era, AI has proved to be the most emerging field with the development of potential systems like Driverless Cars, Intelligent Robots, Smart Bots and many more which have caught the attention of the entire world. Truly speaking, it is hard to believe as if it were all fiction or fantasy. Machine Learning is one of the scopes or sub-domains of Artificial Intelligence but not limited to, can be depicted as here.
Machine Learning is playing a vital role in
meeting critical business requirements by providing business
intelligence. It aptly uses algorithms for making sentiment analysis of
posts, comments, feedbacks on social platforms or portals. Such analysis
helps in identifying users opinions on the products, services, events or any
digital entity. Thus, it has vast potential to uplift social campaigns to a
more promising levels in analyzing our digital assets and boosting their
performances. Whereas Content Management Systems have been in use to uplift and
showcase the Business expertise, services and products to the end
customers.
There are a number of such
functional areas in CMS, where Machine Learning can reinforce and bring up
fruitful results. Various Open Source CMS systems have very basic search
functionality of metadata about digital assets (contents, comments, and etc.)
which may not be helpful in this cut throat competition. Here, Machine Learning can help the CMSs by
making search functionality potential enough to search results from all kind of
contents (Video, Images, or non-textual search for example video clip, or
sample image). Wherein, Deep Learning algorithms
help building such systems that can recognize by images. As the digital assets
are increasing by leaps and bounds and such an advanced search would be
definitely strengthen CMSs in sorting out contents to the users.
For business with content oriented
platforms, it is very important to know the readers sentiment (Positive or
Negative) regarding contents and what actually the reader is looking for. With
recent technology advancements, Machine Learning can help us in predicting
it. We are aware of Amazon’s
Recommendation system for products to consumers such as “Items Frequently
bought together” or “People who bought this also bought this”. Content
Management Systems can have similar implementation for contents and bring more
users to the platform. The system can implement data mining algorithms to fetch
relevant data such as:
- Referral Portals (Identification of the user source or they visited from)
- Users Ratings to the content
- Users most frequently visited pages
- Users Engagement to the content
- Users Reviews to the content
These all adds up to make
inferences for the content to be recommended to users. It is certain that AI
will revolutionalise the way CMS functions beyond our imagination, beyond the
speed we adopt and react, beyond our requirements. It is also going to change the way the
businesses operate.
Many more on application of AI in
CMSs in my future posts.
