Sentiment-Based Latent Space Visualization for Search Results
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Solution Overview
Problem
Existing modem information systems often return search results that are biased towards a single set of ideas, regardless of their validity or accuracy, leading to a lack of diversity in sentiment representation.
Innovation Solution
A system that generates a visualization of records along a sentiment scale, using sentiment scores to determine a weighted mean sentiment and create subranges for positive and negative sentiments, allowing for the selection and display of records based on their sentiment and display scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional search systems retrieve and display search results based on relevance algorithms, then the search results are directed along a single set of ideas, but this leads to a lack of diversity in sentiment representation
Solution Approach 1:
The patent segments the search results visualization by creating distinct regions along a sentiment scale, dividing the display into positive sentiment region, neutral sentiment region, and negative sentiment region. This segmentation allows diverse sentiment representations to be simultaneously presented while maintaining organized structure, directly addressing the contradiction between sentiment diversity and information representation.
Solution Approach 2:
The patent introduces a sentiment dimension to the traditional search results display by mapping records to positions along a sentiment scale. This dimensional transformation enables the visualization to capture sentiment diversity without losing the relevance information, as records are positioned based on both their relevance scores and sentiment scores, resolving the contradiction between diversity and information preservation.
2Ease of operation
If the visualization region is centered around a moving average sentiment, then the visualization shows a balanced view of sentiments, but the region must be wide enough to show clusters representing other sentiments
Solution Approach 1:
The patent implements a dynamic visualization region that automatically adjusts its width and positioning based on the distribution of sentiment scores in the search results. The region is centered around the moving average sentiment but expands to accommodate sentiment clusters, creating a balanced view that adapts to the data characteristics without requiring manual configuration of region width.
3Measurement precision
If sentiment analysis is applied to text content of records, then sentiment scores are determined for each record, but this increases the computational complexity of the search system
Solution Approach 1:
The patent introduces sentiment analysis as an intermediary component that processes search results after the traditional relevance-based retrieval. This intermediary layer applies sentiment scoring to records and integrates the sentiment information with relevance scores for visualization purposes, allowing accurate sentiment measurement while maintaining the existing search system architecture and minimizing overall system complexity.
Data Source
AI summary
A method and related system for visualizing search result information based on sentiment includes operations to retrieve sentiment scores associated with retrieved records associated with display scores and comprising values in a latent space, determining a centering sentiment based on the sentiment scores, and determining sentiment ranges and subranges based on the centering sentiment. The method further includes selecting a first record based on display scores of records within the first subrange, sending data comprising the sentiment range to a client device that causes the client device to present a visualization of a region bounded by the sentiment range. The visualization includes a first shape representing the first record positioned in a first subregion associated with a positive sentiment and a second shape representing a record within the second subrange positioned in a second subregion associated with a negative sentiment.