Two decades ago, businesses could only speculate about what will happen in the future. However, the emergence of sophisticated technology such as machine learning and concepts such as big data have brought forth so much data — it’s now possible to accurately determine future trends.
However, a big chunk of this data is often unstructured. This means that although most businesses today are data-rich, they are unable to utilize the data to achieve their full potential. So, what can you do to maximize the vast amounts of data you have today? Four words — advanced pattern recognition solution.
What is Advanced Pattern Recognition?
Advanced Pattern recognition refers to the process of differentiating sets of data as well as segmenting them based on set criteria. It is one of the most important elements of machine learning. Simply put, pattern recognition is the extraction of consistent trends in a given pattern.
Now, on that note, advanced pattern recognition solutions refer to the specific algorithms used in identifying regularities in a particular set of data. These solutions are the key to extracting or uncovering hidden information from an unstructured collection of data. They allow you to take advantage of the vast amounts of data available today to enhance operational efficiency, make more accurate decisions and, as a result, enhance business growth. The unstructured data itself can be anything from images, texts to sounds.
The Pattern Recognition Process
- It all starts by gathering data from different sources. This can be done through input or tracking.
- The raw data is then cleaned up to make it comprehensible.
- The data is then examined for similarities, commonly referred to as relevant features
- The expert groups it in specific segments depending on the similarities identified in the step above.
- Next, the segments are analyzed and valuable insights extracted.
- Finally, you get a report with essential insights generated from the data that you can use to enhance operational efficiency.
As you can see, the pattern recognition process follows a series of steps to convert unstructured data to comprehensible insights that you could use to promote smooth-sailing plant operations and business growth. Therefore, to achieve this, an advanced pattern recognition solution must have the following:
- A feature extractor to select or clean up the raw data
- A pattern matcher to compare the raw data against the existing reference patterns
- The reference templates memory
- The decision-maker
Advanced Pattern Recognition Solution Applications
Now that you know what pattern recognition is all about, where is it applicable? Well, even though the applications run a wide gamut, recognition solutions are most commonly used in:
- Natural Language Processing
Natural language processing refers to the science of teaching machines to understand human language and generate appropriate responses. Even though it uses a variety of techniques, prediction recognition solutions are often used to break down the raw data, find similar connections, and construct useful variations.
- The Stock Market
Pattern recognition solutions are used in the stock market in the context of data analytics. For instance, in the stock market forecasting, these solutions are used to carry out comparative analysis to predict possible outcomes.
It is also used in audience research to analyze available user data and segment it based on the selected features, mostly provided by Google analytics.
- Optical character recognition
- Visual search and face detection
- Sentiment analysis
- Voice recognition
In a nutshell, pattern recognition is the secret to unlocking the potential of big data. With the help of advanced pattern recognition solutions, you can identify trends that will help you cut on operational costs, enhance business processes, and grow your company today.