Chatbot Hierarchy Map Content Navigation
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Solution Overview
Problem
Users face difficulties in efficiently locating desired content within large and complex content repositories, as existing search methods require manual review of search results and targeted search terms, leading to a need for a more accurate and time-efficient navigation solution.
Innovation Solution
A system and method for dynamically generating a chatbot that uses a hierarchy map of the content repository to create decision-tree based prompts, allowing users to interactively navigate to desired content without manually searching through numerous results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users use traditional search bars to search for content in large content repositories, then they can find content related to their search terms, but they must manually review search results and provide targeted search terms, which increases time consumption and operational complexity
Solution Approach 1:
The chatbot performs the search and navigation tasks automatically based on user natural language queries. The system extracts intent from user messages, traverses the hierarchical content structure autonomously, and presents relevant content without requiring users to manually review search results or construct complex search queries, thereby reducing time loss and improving productivity
Solution Approach 2:
The patent replaces the mechanical manual search process with an automated chatbot system. Instead of users manually browsing through search results, the chatbot uses natural language processing and hierarchical data structure traversal to automatically locate and present content, substituting manual mechanical operations with automated intelligent processing
2Quantity of substance
If content repositories become broader to store more information, then they can accommodate larger volumes of data, but it becomes more difficult for users to locate desired content within the expanded repository
Solution Approach 1:
The patent segments the content repository into a hierarchical structure with multiple levels (parent categories, sub-categories, and individual content items). This segmentation organizes the large volume of information into manageable sections, making it easier for users to navigate and locate specific content through the chatbot's guided traversal of the hierarchical structure
Solution Approach 2:
The chatbot acts as an intermediary between the user and the large content repository. It processes user natural language queries, translates them into navigational actions within the hierarchical structure, and presents relevant content. This intermediary layer simplifies the interaction, making the repository easier to operate despite its broad scope and large information volume
3Measurement precision
If users manually review search results to identify desired content, then they can find accurate matches, but the process becomes more time-consuming and requires more user effort
Solution Approach 1:
The chatbot implements an iterative feedback mechanism where it presents content items to the user and receives feedback on relevance. Based on this feedback, the chatbot adjusts its search strategy and refines subsequent results. This feedback loop ensures high measurement precision in identifying desired content while reducing time loss by automatically adapting to user needs without requiring manual review of numerous search results
Data Source
AI summary
Provided herein are methods and systems for generating a chatbot. In response to a user selection of a content repository, the method can include generating a hierarchy map based on the selected content repository, translating the hierarchy map into a series of chatbot prompts, and generating a chatbot based on the series of chatbot prompts. The chatbot can be configured to guide the user to selected content within the content repository.