Hi @SrikanthManthina ,
To implement the functionality of suggesting matching entries based on previous correspondence and frequently contacted people in your desktop application, you can follow these steps:
1. Collect and store contact data: Start by collecting and storing relevant contact data from your application, such as user profiles, email addresses, and previous correspondence. This data will be used to determine frequent contacts.
2. Implement the search UI: Create a search input box in your desktop application where users can enter their search queries.
3. Capture user input: Listen for user input events on the search box and capture the text entered by the user as they type.
4. Determine frequent contacts: Analyze the stored contact data to identify frequently contacted people. You can keep track of the frequency of communication or other relevant metrics to determine the level of contact.
5. Generate suggestions: As the user enters their query, match the entered text with the stored contact data. Prioritize and display suggestions based on both the user's input and the identified frequent contacts. This can include names, email addresses, or any other relevant information.
6. Update suggestions dynamically: Continuously update the suggestion list as the user continues to type or modifies their search query. Reapply the search logic and recalculate the suggestion list based on the new input.
7. Display suggestion dropdown: Show the generated suggestions in a dropdown or autocomplete menu below the search box as the user types. Ensure that the suggestions reflect both the user's input and the frequent contacts.
8. Handle suggestion selection: Allow users to select a suggestion from the dropdown by clicking or navigating through the list using arrow keys. When a suggestion is selected, populate the search box with the selected name or email address.
9. Perform the search operation: When the user submits the search query or selects a suggestion, use the entered text to perform the desired search operation in your application (e.g., retrieving relevant data, filtering results, etc.).
10. Refine contact data over time: Continuously analyze user interactions and feedback to improve the accuracy of frequent contacts. Monitor communication patterns, track successful and unsuccessful searches, and update the contact data based on user behavior.
By following these steps, you can implement the functionality of suggesting matching entries based on previous correspondence and frequent contacts in your desktop application, similar to the Teams search bar.
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Both Microsoft Teams and Outlook provide APIs that allow developers to integrate their functionality into their own applications. These APIs can be used to access and manipulate data stored in Teams and Outlook, as well as leverage various features and capabilities of these platforms.
Microsoft Teams API:
The Microsoft Teams API allows developers to build apps that interact with Teams, enabling features such as creating and managing teams, channels, and chat messages. It also provides access to user and organization information, allowing developers to integrate Teams functionality into their own applications.
Outlook API:
The Outlook API provides a way to access and manipulate data stored in Outlook, such as emails, calendar events, contacts, and more. With this API, developers can create applications that can send and receive emails, manage calendar events, and perform various other tasks related to Outlook functionality.
By utilizing these APIs, you can leverage the heavy lifting performed by Teams and Outlook, accessing data efficiently and reusing their functionality within your own application.
If I have answered your question, please mark your post as Solved If you like my response, please give it a Like Appreciate your Kudos! Proud to contribute! :) |