Snippet Module for Social Network Entity Summarization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Social networking systems face challenges in efficiently summarizing large volumes of user-generated content related to entities, such as restaurants or events, making it difficult for users to quickly make informed decisions without sifting through extensive information.
Innovation Solution
A snippet-module is generated within the social networking system to display a curated list of top-scoring noun phrases extracted from posts associated with an entity, using techniques like TF-IDF scoring and filtering to highlight relevant information, reducing the noise and presenting only the most informative content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all user-generated content objects are displayed to users, then information completeness is improved, but information overload and user decision-making difficulty worsen
Solution Approach 1:
The system extracts only the most relevant noun phrases from user-generated content using TF-IDF scoring and frequency analysis. This extraction process isolates key information entities (e.g., menu items, services, features) from the full text corpus, presenting only essential information to users while maintaining information completeness for decision-making
Solution Approach 2:
The patent introduces an intermediary processing layer between the full content corpus and the user interface. This layer includes modules for text normalization, entity extraction, frequency counting, and relevance scoring that mediate between raw user-generated content and the simplified snippet display, transforming complex information into digestible formats
2Loss of information
If extensive user-generated content is presented to users, then information completeness is improved, but time required for information processing worsens
Solution Approach 1:
The system performs preliminary processing of user-generated content in advance, including text normalization, entity extraction, and frequency analysis. By pre-computing TF-IDF scores and identifying top-frequency noun phrases before user interaction, the system prepares summarized information ready for immediate display, eliminating the need for real-time processing during user queries
Solution Approach 2:
The system extracts only the most relevant noun phrases from user-generated content using TF-IDF scoring and frequency analysis. This extraction process isolates key information entities (e.g., menu items, services, features) from the full text corpus, presenting only essential information to users while maintaining information completeness for decision-making
3Productivity
If a snippet-module with extracted noun phrases is generated, then information processing speed is improved, but information completeness may worsen
Solution Approach 1:
The system changes the parameter of information representation from full text to extracted noun phrases with associated frequency metrics. By transforming continuous text into discrete, countable entities and applying TF-IDF scoring, the system maintains essential information characteristics while enabling rapid processing and comparison of key concepts across multiple content objects
Data Source
AI summary
In one embodiment, a method includes accessing posts of an online social network, each post being associated with a first entity of the online social network, classifying, based on content and metadata associated with each post, one or more of the posts as being relevant to the first entity, extracting a set of one or more n-grams from the content of the posts classified as being relevant to the first entity, filtering the set of n-grams to remove one or more of the extracted n-grams from the set of n-grams, calculating a quality score for each n-gram in the filtered set of n-grams, generating a snippet-module including one or more of the extracted n-grams from the filtered set of n-grams having quality-scores greater than a threshold quality-score, and sending, to a client system of a first user of the online social network, the snippet-module for display to the user.