Information Retrieval and Affinity Grouping – Gen AI
Introduction
In today's digital age, online meeting applications have revolutionized the way we communicate and collaborate remotely.
These platforms, such as Google Meet, Zoom, Microsoft Teams, and others, offer a seamless and immersive experience for virtual meetings, webinars, conferences, and collaborative work sessions.
Yet the way of gathering knowledge via these platforms can be improvised. Some of these features can be Information Retrieval System and Affinity Grouping System that helps the user to utilize the meeting efficiently.
Challenge
The current method of organizing suggestions and ideas in online meetings lacks structure and efficiency, leading to scattered discussions and difficulties in decision-making. Accessing relevant information during online meetings is time-consuming and often requires manual search efforts, leading to delays and inefficiencies.
Affinity Grouping
Affinity grouping is a method used to organize items or entities based on their shared characteristics or similarities. It involves categorizing things into groups or clusters that have common traits or attributes. With the help of this technique, we can efficiently group the suggestions shared by the attendees from the meeting and respond to these grouped suggestions accordingly.
Information Retrieval
The task of information retrieval involves retrieving relevant information from a given document or dataset based on specific queries or questions asked by the user from the meeting. It requires understanding the context of the given document using OCR concepts and using techniques like keyword matching, natural language processing, and machine learning algorithms to extract and present the most relevant information.
Solutions
To address these challenges an AI and ML based approach can be used to make the user experience better.
For Affinity Grouping, the suggestions made by the users from the meeting will be collected and sent to a pre-trained AI model for processing. Which then understands the given meeting notes and group them based on the content spoken in these meeting notes.
For Information Retrieval, the host will upload a document regarding the session and the topics that will be discussed in that session. By harnessing the OCR technique, the data from the document is first retrieved. With this extracted data along with the user question is sent to an AI model. The model then understands the provided data and responds to the user’s question in a summarized manner.
Advantages
Combining affinity grouping and information retrieval in an online meeting can offer several advantages:
Organized Discussions
Affinity grouping helps organize the suggestions and ideas generated during the meeting into categories based on their similarities. This can streamline discussions by focusing on related topics at the right time, leading to more productive meetings.
Improved Decision Making
By grouping suggestions into categories, decision-makers can easily identify common themes or trends. This structured approach enables informed decision-making based on the collective insights and opinions shared during the meeting.
Efficient Knowledge Sharing
Information retrieval complements affinity grouping by providing quick access to relevant information from documents or data sources. During the meeting, participants can ask questions related to the discussed topics, and the system can retrieve and present the necessary information in real-time, enhancing knowledge sharing and understanding.
Faster Problem Resolution
In case of queries or uncertainties during the meeting, information retrieval can swiftly provide answers or clarifications from the available documents or knowledge bases. This accelerates problem-solving and ensures that discussions progress smoothly without delays due to information gaps.
Enhanced Engagement
The combination of affinity grouping, and information retrieval encourages active participation and engagement from meeting participants. Clear categorization of suggestions and easy access to relevant information make it easier for attendees to contribute meaningfully and stay focused on meeting objectives.
Documentation and Follow-up
Affinity grouping can also assist in organizing meeting notes and outcomes into structured formats, making it easier to document decisions, action items, and follow-up tasks. Information retrieval can then be used to retrieve specific details or references during subsequent meetings or for reference purposes.
Overall, leveraging affinity grouping and information retrieval in online meetings promotes organization, collaboration, knowledge sharing, and effective decision-making, leading to more efficient and productive virtual discussions.
Conclusion
Combining affinity grouping and information retrieval in online meetings optimizes discussions by organizing suggestions effectively, enabling informed decision-making, fostering efficient knowledge sharing and problem-solving, enhancing participant engagement, and facilitating documentation and follow-up, ultimately leading to more productive and successful virtual meetings.