Social Snippet Augmentation for Search Relevance
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Solution Overview
Problem
Search interfaces often lack personalized and relevant information about entities related to search queries, leading to inefficient user interaction and exploration of search results.
Innovation Solution
The system retrieves and augments social snippets by identifying entities associated with search queries, assigning quality scores to taglines, and incorporating commonalities between users and entities to create personalized and relevant augmented social snippets for display in search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional search interfaces are used, then search results can be displayed efficiently, but user interaction and exploration become less engaging and informative
Solution Approach 1:
The patent introduces social snippets as an intermediary element between traditional search results and user information needs. These social snippets act as a mediator that bridges the gap by incorporating social graph data, user profiles, and contextual information into the search results display, thereby enhancing user interaction while maintaining efficient search functionality.
Solution Approach 2:
The search interface is enhanced to perform multiple functions simultaneously: it displays traditional search results while also presenting personalized social snippets, commonality indicators, and entity relationships. This multi-functional approach allows the same interface to serve both efficient search and engaging user interaction purposes.
2Productivity
If search results are displayed as a list with titles and snippets, then information can be reviewed efficiently, but personalized and relevant information about entities is lacking
Solution Approach 1:
The patent applies local quality by customizing the search results display based on the specific entity being searched for. Instead of a uniform list view, the system dynamically generates personalized social snippets and commonality indicators tailored to each entity, thereby maintaining efficient information review while adding relevant personalized content.
Solution Approach 2:
The search results interface is made dynamic by automatically adjusting its content based on real-time analysis of the search query, entity data, and user profile. The system dynamically generates and updates social snippets, commonality indicators, and relationship information, allowing the interface to adapt to different search contexts while maintaining efficiency.
3Loss of information
If entities are identified and taglines are retrieved from multiple sources, then relevant information can be gathered, but the system complexity increases
Solution Approach 1:
The patent segments the information gathering process into distinct modules: entity identification, tagline retrieval from multiple sources, quality scoring, and social snippet generation. Each module handles a specific aspect of the complex task independently, making the overall system more manageable while effectively gathering comprehensive relevant information.
Solution Approach 2:
The quality scoring mechanism acts as an intermediary that filters and prioritizes information from multiple sources before it is used to generate social snippets. This intermediary layer simplifies the complexity by automatically filtering out low-quality information and focusing on the most relevant taglines, thereby reducing the cognitive load on the system.
Data Source
AI summary
One or more techniques and/or systems are provided for augmenting a social snippet with an augmentation tagline. For example, a search user may submit a search query through a search interface (e.g., “algebra help” search query). An entity associated with the search query may be identified (e.g., a math professor). A set of taglines associated with the entity may be retrieved (e.g., descriptive information about the math professor extracted from social networks, documents, websites, etc.). A social snippet for the entity may be augmented with an augmentation tagline selected from the set of taglines or generated based upon information relating to the entity. The augmented social snippet may be displayed through the search interface, and the augmentation tagline may indicate a relevance of the entity to the search user (e.g., an indication that the math professor teaches algebra at a university attended by the search user).