Today most organizations gather and produce a huge amount of data daily. Most of this data is processed to come to many meaningful and actionable insights for the company. The sheer voluminous quantities of data create an opportunity and a challenge to concentrate on the necessary information. To tackle this, process such as text mining and image mining have been introduced, which transforms unstructured data into structured data for accurate analysis.
Text mining and image mining are fields that have progressed rapidly in the last few years. They also hold a lot of possibilities for real-world usage that could benefit the operations of organizations. Both belong to the interdisciplinary fields constituting data mining, statistics, machine learning, and artificial intelligence; and are concerned with the process of extraction, analysis, and knowledge discovery in digital images and texts.
Here is a look at the best real-world use cases for Image mining and text mining and their implications on business:
Image mining is primarily involved with the extraction of images from a collection of images. Unlike other processing techniques, Image mining focuses on the extraction of patterns, clusters, and relationships from a large set of images. They are used in a variety of situations in several industries.
3 use cases of image mining are:
a. Classification of images for improved search: The internet is the biggest repository of very huge amounts of data including images and gives access to everybody in the world who needs knowledge. From the internet, we can easily obtain digital images of various kinds of real-world scenes. Presently, however, classification /recognition of generic real-world images is far from practical due to the multiplicity and the authenticity of real-world scenes. Such diversity can be categorized and classified with the help of Image mining. Furthermore, Generic image classification using images automatically gathered from the internet can help companies with copyright claims, retrieval of images, and a more precise search result.
b. Image mining for Medical Diagnosis: Image mining can assist medical professionals with detection of a variety of ailments such as tumours, MRI scans, Eye related diseases. It can help in analyzing medical images with high accuracy when dealing with human life. Nowadays, Systems that utilize image mining are being built to offer medical professionals’ trouble-free access to the screening and trends associated with a myriad of diseases. For instance, Image mining is applied in the domains such as breast mammograms to classify and detect cancerous tissue.
c. Image Mining in Natural Scene Recognition: Image mining methods are used in natural scene recognition as they consider patch appearances and their relationships to form natural scene recognition. For example, a ‘beach’ scene can be characterized by a ‘sky’ region above ‘sand’, and a ‘water’ region between ‘sky’ and ‘sand’. This method renders each image as a spatial pyramid, from which we attain a set of patch appearances with spatial layout information. Each image is represented in this manner, from which a collection of data regarding the appearance and layout is obtained. Then they apply a feature mining approach to get discriminative patch combinations. The extracted patch combinations can be interpreted as adjectives or prepositions, which will be used for scene understanding and recognition.
Text mining is the process of translating large quantities of unstructured data by using technologies such as AI to automatically process data and produce actionable insights to make accurate decisions. Some techniques such as categorization, entity extraction, sentiment analysis, and others, help in the extraction of useful information and knowledge hidden in-text content with Text mining. As the relatively new area of computer science, it has gained widespread adoption across industries.
3 Use cases of text mining are:
a. Restriction of Cybercrime: As more data and operations are flowing online, it can contribute to the increased risk of cybercrimes such as phishing, bullying and data breach. Companies can prevent this by using the Text mining capabilities in cybersecurity apps to spot malicious activities. It can also analyze and identify the words used for bullying, threats, and harmful activities on the internet. This makes internet crime prevention easier for any enterprise and law enforcement or intelligence agencies.
b. Customer Care Service: Today, customer care deals with a high volume of requests and queries that can be very hard to tackle in real-time. Some of the well-known applications for customer care are Text mining and natural language processing to enhance the experience of the customer. Many methods such as polls, case tickets, and customer call records help to improve the overall efficiency and quality of resolution for the customer. Text mining also provides a fast, automated reply to the queries. This is vital to developing and driving customer experience and brand image.
c. Risk Management: An important part of success for any organization is managing and mitigating risk. This is relevant especially in the financial industry, where there is a huge scope of improving the ability to mitigate risk with the adoption of Risk Management software that utilizes text mining. This enables the entire control and management of the sources and text documents that are stored in petabytes, thus giving the capability to link together and access the exact information needed at the right time.
Apexon is a global leader in Data science and analytics. We help companies understand and utilize the power of their data. Our Text Mining and Image Mining capabilities will help you mine critical information to produce data-driven decisions. To know more, visit Apexon.com
About the author:
Vice President – Healthcare and Data Science
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