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❯Entertainment and Media - Search Optimization
Large Companies
NLP - Text summarization
For:
Media Intelligence Analysts
Scope:
Using Abstractive Text Summarization to reduce analysis costs for media monitoring.
Goal:
Improve Operation Efficiency
AI virtual assistant for customer support and service
For:
Customer service department
Scope:
Customer support service, product and service consulting.
Limitations - support for dialogs exclusively within MTS products.
Target audience - b2b, b2c clients of MTS Russia.
Goal:
Other
AI contract management
For:
Procurement department, legal department
Scope:
Building an AI contract management solution for automating business processes
related to documents: data classification, automatic data extraction and contract
monitoring.
Goal:
Other
Large Companies
Small Companies
Human Resources - Employee Performance Assessment
For:
Line managers.
Scope:
Creating an insight report for managers carrying out employee performance reports using Text Mining.
Goal:
Improved Employee Efficiency
Virtual bank assistant
Scope:
Use of advanced chatbots and dialogue systems to automatize part of call centre activities.
Goal:
Improved Employee Efficiency, Improved Customer Experience
General Public
Entertainment and Media - Search Optimization
For:
End consumers of news stories.
Scope:
Optimizing search using Machine Learning and Natural Language Processing to improve relevancy and presentation of results.
Goal:
Improved Customer Experience
Large Companies
NLP - Machine translation
For:
Translation Managers and Translators.
Scope:
Using Machine Translation to scale content production and create a more streamlined and efficient translation process.
Goal:
Improve Operation Efficiency, Automate a Business Process
Loan in 7 minutes
For:
Customers
Scope:
A completely automated solution that analyses customer behaviour and makes the best loan offers for the customer.
Goal:
Improved Customer Experience, Improved Employee Efficiency
Large Companies
Small Companies
Legal - Automated Legal Review
For:
Legal Associates and Paralegals.
Scope:
Supporting human analysis of legal documents using automated Document Classification and Information Extraction.
Goal:
Improve Operation Efficiency, Improved Operation
Procurement - Cost Analysis
For:
VP Global Supply Chain Management, Category Managers
Scope:
Realizing operational efficiencies and working capital improvements through automated spend classification.
Goal:
Reduce costs, Improved Employee Efficiency
Tax rules updates and classification
For:
Investment firm
Scope:
Build an AI solution that identifies updates on tax laws and classifies them.
Goal:
Other
Procurement - Supplier Selection and Evaluation
For:
Procurement Managers
Scope:
Creating efficiencies in supplier selection using Intelligent Search technologies.
Goal:
Improved Employee Efficiency
Large Companies
Retail - Customer Sentiment Analysis
For:
Retail managers, executives, marketeers and branding specialists.
Scope:
Understanding consumer sentiment towards national grocery chains in South Africa using Natural Language Processing.
Goal:
Improved Customer Experience
WebioMed clinical decision support system
For:
End-users (physician, nurse, laboratory technologist, pharmacist, patient)
Sales and marketing team
CDSS product development and maintenance team (system administrator,
system developer, system architect, project manager, and system
maintenance)
Scope:
Screening for cardiovascular disease risk prediction with machine and deep
learning methods
Goal:
Other
Large Companies
Human resources - Federate the team
For:
HR professionals.
Scope:
Using Artificial Intelligence (AI) to identify ideal candidates, decrease hiring time and improve employee retention.
Goal:
Improved Customer Experience
Large Companies
Small Companies
Legal - Contract Analysis
For:
Legal Associates and Paralegals.
Scope:
Using natural language processing to aid contract analysis by creating efficiencies for reviewers.
Goal:
Improved Employee Efficiency, Reduce costs, Improve Operation Efficiency
General Public
Entertainment and Media - Search Optimization
For:
End consumers of news stories.Goal:
Improved Customer ExperienceProblem addressed
The ability to search efficiently through news content is of primary importance for end users of news sites. Often the sheer amount of information that is indexed, which can be updated at sub minute intervals, can be overwhelming.
Search is typically one of the first features a user will interact with on a news website. Results have to be relevant to the input query. Determining how well a result matches the query typically requires a scoring function that is difficult to define with rules and heuristics alone. Click feedback and analytics is required to ensure quality of results. Good quality search will drive engagement and time on site.
Scope of use case
Optimizing search using Machine Learning and Natural Language Processing to improve relevancy and presentation of results.
Description
Machine learning algorithms, trained on user inputs and click feedback, are commonly used to score candidate results. Manual annotation of result sets is often used to further optimize search relevancy. Natural Language Processing techniques are also often used to both analyze the input query before searching against the index and for organizing the results into related themes for the end user.
On the Bloomberg terminal, 17 news stories a second are published1. Bloomberg uses proprietary AI models to prevent users from becoming overwhelmed by results. Firstly, a model groups similar results together, while a second model then assigns a summary to each result cluster. To make navigation easier for the end user, instead of a long list of results, the Bloomberg user interface presents the clusters as “Key Themes” that can be further drilled into.
Nowadays many enterprise search solutions offer tunable search relevancy straight out of the box with no coding required.
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AI: Perceive
Machine Learning
Search & Discovery
AI: Understand
Retrieve Information
AI: Act