Knowledge Mining – The New Stream in Intelligent Content Search

The digital transformation wave has fueled organizational growth opportunities by leveraging the power of cloud, data, and AI. As we know the enormity of data generated on a day-to-day basis, the challenge is to find the right set of information from the various content assets compiled in the form of images, pdfs, and videos.

The AI-powered technologies empower the organizations to glean knowledge from their content assets in reduced time with more precision and exacerbate business performance. Now, enterprises embrace knowledge mining to unlock the hidden information in their data and make it available to the end-users.

 What Led to Disruption in Content Search?

As there is a heap of unstructured data available, the organization still find challenges in using the data in a meaningful way. It was a strong point that needed attention and a solution. The need to explore unstructured data in a significant way to be used for the organizational benefit led to the innovative disruption called Intelligent Search.

Here are the few pain points, as per the Harvard Business Review, that led businesses to think about a new method of content exploration:

• More than half of the data available is in unstructured format hiding the visibility of the critical information that could be a potential source for the organization.
• Information trapped in the content assets like PDF, documents etc., can be in either semi-structured or unstructured format.
• Unstructured data could be a source of critical-business information that can help give insights into the business performance, workflow process, patterns & trends for making predictions and improving customer experience.
• Overcoming the manual process of interpreting information that is time-consuming, tedious, and prone to human error.

 How Knowledge Mining Works?

 Knowledge Mining, a branch of AI, uses intelligent services to gather information from vast amounts of data to unlock hidden insights and recognize the patterns at scale. It helps extract key information from the unstructured data available as videos, images, paper documents, pdfs, or hand notes. Thus, knowledge mining helps uncover insights from all structured and unstructured data and allows organizations to glean knowledge from critical content assets.

 Three phases in Knowledge Mining

The AI capabilities of Knowledge Mining deliver faster insights and enhanced experience to the end-users in the organization; however, there are three phases in knowledge mining that help maintain data accuracy and relevancy throughout its lifecycle.

The knowledge mining using Azure is described as follows:

• Ingestion: in this process, the raw data (structured or unstructured) is collected into a data store. At the end of the process, the relevant information is extracted using OCR, especially when data needs to be extracted from PDF or image files.

• Enrichment: Pre-built AI capabilities like vision, speech, language recognition, sentiment analysis, translation, etc., are used in this phase to identify patterns and understand the texts coming from the unstructured sources. 

• Exploration: In this stage, the enriched data is made available through search indexes or CRM or ERP systems. Post this process, analytical tools like Power BI is used to gain further knowledge from the gathered information.

Key Benefits Drawn from Knowledge Mining

 The AI-Based search helps overcome the traditional method of extracting valuable information from the data store, which is ineffective and time-consuming. Here are the few benefits of leveraging Knowledge Mining:

• Repetitive processing tasks become easier
• Negligible error
• Results and insights are obtained faster
• Links between different data can be easily found

Industries That Can Benefit With Knowledge Mining 

Knowledge mining can help uncover hidden insights from the organizational data assets and unlock newer business growth opportunities. Here is the list of the businesses/industries that can reap full-fledged benefits from this AI-based solution.

Media and Telecom

The media and telecommunication industry deals with enormous data in the form of transcripts or phone calls. Leveraging Knowledge mining and cognitive services can help find various information through the analysis of the communication forms. Moreover, it can also be used to measure an employee's KPI's, followed by training and assessments, to improve customer engagement and build better strategies.

 Legal

The legal sector can use this solution to search for a ton of documents. Knowledge mining can scan and analyze several documents like legal papers, claims, policies, invoices, manuscripts, images, etc. It can help extract valuable information that may go unnoticed by human eyes, thereby easing the investigations.

 Insurance and Finance

As the finance sector deals with several documents related to accounts, knowledge mining can help link data from unrelated documents and contribute to critical decision-making and better predictions to efficiently act upon the trends. Furthermore, intelligent search solutions can offer a better customer experience, such as smart banking and smart consulting. For example, the scanning of customer ID cards will retrieve all the minute details about the individual seamlessly, without any error, and in no time.

 Logistics

In the logistics sector, knowledge mining solutions could be useful to analyze information from unstructured data obtained from the RSS services and other data sources. This AI-based solution can pull relevant information related to the shipping time, predict delays, or prepare optimal delivery routes that can be useful during crucial situations.

 Retail

The retail sector handles many receipts for the purchases and needs to add loyalty points to the customers' accounts for their purchases. Knowledge mining with OCR can be useful in scanning the receipts and automatically adding the loyalty points. This AI-based search can improve customer experience and engagement.

 Manufacturing and Engineering

For the manufacturing and engineering departments, leveraging the knowledge mining can help get technical documents handy. To get an essential technical report could be cumbersome when done manually. However, the intelligent search can save a lot of time for the team and enhance efficiency and productivity. Searching service history and production line manuals become seamless with knowledge mining.

Pactera EDGE’s Cognitive Search Service Platform

Knowledge Mining Engine (KME) is Pactera EDGE’s cognitive search service platform that comprises of APIs, which can be used for extracting relevant information from big and diverse data sets for users in their work context e.g. Text Mining, Document Mining & Image recognition. 

 Cognitive Service Platform Solutions

 Text Search

·        Key phrase

·        Text Analytics

·        Language Translation

·        Content Moderator

Image Recognition  

·        Computer Vision 

·        Custom Vision 

·        Face Recognition  

·        Video Indexer 

Conclusion

Data needs to be harvested to unlock the opportunities for business development. Many business leaders now believe that unstructured data can create value for the organization, and it can be achieved by using intelligent search solutions like knowledge mining. Pactera EDGE can be an entrusted partner in developing a robust knowledge mining solution for organizations to overcome the key challenges of time, scale, and insights. 

 Image Source: https://daniel-krzyczkowski.github.io/How-To-Build-Knowledge-Mining-Solution-On-The-Azure-Cloud/