Intent Engine for Social Network Message Relevance
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Solution Overview
Problem
Current search engines face challenges in providing effective and relevant search results from social network data, as they lack the ability to accurately detect user intent from natural language queries.
Innovation Solution
An intelligent intent engine is developed to analyze user messages on social networks, detect user intent, and generate filtered answers by processing natural language inputs, allowing users to access relevant information through a specialized relationship within the social network, enhancing the relevance of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If search engines process social network data without intent detection, then data processing capability is maintained, but search result relevance deteriorates
Solution Approach 1:
The patent introduces an intent detection engine as an intermediary component between social network data processing and search result generation. This mediator analyzes user messages to extract intent information, which then filters and refines search results. The intermediary resolves the contradiction by adding a specialized layer that improves relevance without requiring complete system redesign.
Solution Approach 2:
The system segments the search processing into distinct modules: social network data collection, intent detection engine, and search result generation. By dividing the complex task into separate functional segments, the patent manages complexity while improving relevance through focused intent analysis in the detection engine.
2Measurement precision
If the system processes natural language queries without specialized intent analysis, then processing speed is maintained, but query understanding accuracy deteriorates
Solution Approach 1:
The intent detection engine performs preliminary analysis of user messages before search query processing begins. By extracting and storing intent information in advance, the system enables faster subsequent query processing while maintaining high accuracy in understanding user intentions through pre-computed intent models.
3Ease of operation
If search engines provide general search results, then system simplicity is maintained, but user experience quality deteriorates
Solution Approach 1:
The system incorporates feedback mechanisms where users interact with search results, and this interaction data feeds back into the intent detection engine. The feedback loop continuously refines intent models and improves search result relevance, enhancing user experience while managing complexity through iterative optimization rather than monolithic design.
Data Source
AI summary
An intent engine that automatically detects user intent from messages of a social network (e.g., messages with questions to ask) and outputs intent data. The engine is intelligent in that it can process natural language input such as questions and terms. The user is then directed to an answer page filtered according to the intent data and which provides answers related to a question, for example. The intent engine can be designated (e.g., tagged, or “friended”) and then linked into a specialized relationship (e.g., a “friend”). Accordingly, in one example, a URL link is constructed that points to the answer page, with filters configured based on the intent data. The URL is then sent back to the user as a friendly response. When the user selects the link, the user is presented with an answer page that provides answers which match the user intent derived from the user messages.