We generally categorize everything that we come across in life, for example, we group books, music, and movies into specific genres based on their special characteristics. Digitization has helped apply the same concept to online content such as web pages, blog posts, news, e-books, and other learning content. With the immense increase in online availability of information, data needs to be found easily and analyzed faster. This is where content categorization steps in.
Content categorization helps in assigning web content into multiple categories and further divides them into sub-categories. This way diverse data can be sorted into meaningful groups. It helps in content structuring and easier accessibility of information on websites.
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Categorization helps with accessibility and streamlining processes
Content categorization is identifying groups of elements in texts, based on a defined set of features. With the help of text classification, data is analyzed to find specific features to classify content correctly. The categories may range from Travel to Medical to Sports. Finding content becomes easier through categorization, which further speeds up the process of taking an action, i.e. help with a business decision, or research and development. The true challenge is to expect how users are going to look for the information, as the quality of categorization may make or break the findability of a piece of content.
Categorization helps with easy search and navigation of a website or application. So, the application is highly useful in industries like Media & Publishing, E-commerce, Fashion, etc., as categorization helps to improve browsing and identifying similar content on websites.
Content categorization helps assign web content into multiple categories
For improved content availability and accuracy
Effective categorization reduces the cost of content management and improves the operational efficiency of a website. It helps companies to understand how a piece of content should be used. Due to the reduced time in finding information, the duration of actual work increases. The process of automatic categorization makes content easily findable and actionable. And, this is important for companies with a high dependency on customers to find accurate information quickly.
Categorization offers a comprehensive framework for all kinds of content. For marketers, it provides the guidance needed to create the right kind of content that stimulates reader interaction. And, for researchers, it provides a clear foundation to explore their chosen field of study.
Content categorization is a difficult process as it requires content management of a large volume of enterprise information. The changing regulations and compliance issues also make it challenging. Considering these issues content categorization can only be successful when automated categorization techniques and processes are applied. By effectively analyzing unstructured content, companies can categorize previously untapped information so that they are found and used effectively.
Content categorization with machine learning
When content is categorized automatically rules are applied more consistently, the process is faster, it’s not dependent on humans, and therefore is more cost-effective. Machine learning models can help to analyze and leverage text data. They categorize content more precisely, making it easier to access and use. Text Classification is a fundamental task that comes under Natural Language Processing, which has broad applications such as topic labeling and sentiment analysis.
Machine learning models mathematically analyze example documents that are provided to calculate concepts that can be used to categorize the content. It’s not just the words that are analyzed, but also the context and related metadata. For example, let’s say a model is trying to predict the probability of web content being of the ‘Medical’ category. The model checks the underlying Html and interprets its meaning. It analyzes the Html data along with all the links and images related to the website. A mapping of all the features on the website decides the probability of that website belonging to a particular category. It's similar to how a human would decide a category to fit something. From the features extracted from a web page, the model decides the probability of it matching to a particular category.
Content categorization powered by deep learning enables organizations to understand the content that exists with them and helps in effective information management. Access to content is simplified by categorization; it improves information accuracy, therefore reducing search time. Continuous improvement in machine learning techniques is expected to provide more accurate content categorization, enabling organizations to enhance their decision making.
Skyl.ai offers easy to understand machine learning workflows for effective content categorization. Try out our powerful Natural Language Processing platform to build and deploy your own content classification model.
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