Entity-Based Topic Generation for Centralized Information Access
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Solution Overview
Problem
Users face the challenge of obtaining diverse and scattered information on a specific topic due to the need to search for multiple keywords across different sources, leading to inefficiency and a lack of centralized access.
Innovation Solution
An information obtaining method that automatically extracts entity words and associated words from original content, generates topics based on these words, and aggregates relevant information, allowing users to access specific content directly without manual keyword searching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users search for multiple related keywords one by one in news applications or web pages, then they can obtain information of a same subject or topic, but the operation becomes cumbersome and time-consuming
Solution Approach 1:
The system performs preliminary action by automatically extracting entity words and associated words from original information content before user query. The topic generation unit creates topics based on extracted keywords in advance, so when users need information, the topics are already prepared and can be directly displayed without requiring users to manually search through multiple keywords across different sources
Solution Approach 2:
The patent introduces an intermediary mechanism - the topic generation unit that acts as a mediator between the original information content and user queries. This intermediary automatically extracts entity words and associated words, generates relevant topics, and aggregates corresponding information, thereby eliminating the need for users to manually search through multiple keywords and different sources
2Loss of information
If users search for keywords in multiple different news applications or web pages, then they can obtain comprehensive information, but the information becomes scattered and cannot be centrally read
Solution Approach 1:
The patent applies merging by aggregating information from multiple different news applications and web pages into a single centralized topic page. The information aggregation unit collects corresponding information related to generated topics from various sources and presents it in a unified manner, allowing users to read comprehensive information centrally without needing to visit multiple different applications or web pages
Solution Approach 2:
The topic generation unit serves as an intermediary that collects information from multiple scattered sources and organizes it into a centralized structure. This intermediary mechanism aggregates information from different news applications and web pages, making it accessible in one location rather than requiring users to navigate through multiple separate sources
3Measurement precision
If topics are generated manually with related phrases or sentences, then users can access specific content, but manual configuration is required and errors may occur
Solution Approach 1:
The system implements self-service by automatically extracting entity words and associated words from original information content without requiring manual intervention. The extraction unit and topic generation unit work autonomously to identify relevant keywords and create topics, eliminating the need for manual configuration while reducing errors associated with human input
Solution Approach 2:
The patent replaces the mechanical system of manual keyword configuration with an automated computational system. Instead of requiring users to manually enter related phrases or sentences, the system uses automated text extraction and topic generation algorithms to create topics, thereby improving accuracy while reducing operational complexity
4Ease of manufacture
If a single entity word is used to generate a topic, then the topic generation is simple, but the topic covers an excessively wide range and cannot locate specific hot spot content
Solution Approach 1:
The patent applies merging by combining multiple entity words and associated words to generate topics. Instead of using a single entity word that creates overly broad topics, the system merges multiple related keywords into comprehensive topics that maintain both simplicity in generation and specificity in content location, enabling accurate identification of hot spot content
Data Source
AI summary
This application discloses information obtaining methods and related devices and systems. An example information obtaining method includes extracting a plurality of entity words and an associated word associated with the plurality of entity words from original information content. The method further includes generating one or more topics based on the plurality of extracted entity words. The method further includes aggregating corresponding information related to the one or more topics based on the plurality of extracted entity words and the associated word that correspond to the one or more topics. The one or more topics each include at least two entity words.