Review Excerpt Extraction via Attribute Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Consumers face difficulty in extracting useful information from a large number of diverse reviews when researching items for purchase, as existing systems do not efficiently summarize or prioritize relevant review excerpts based on consumer preferences.
Innovation Solution
The implementation of a review extractor system that categorizes reviews based on item attributes, ranks categories according to consumer preferences, and extracts representative review excerpts using semantic analysis to provide concise and relevant information to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a large number of reviews are provided to customers, then the information completeness is improved, but the information processing difficulty increases
Solution Approach 1:
The patent segments the large volume of reviews into distinct categories based on item attributes (e.g., quality, price, durability). Each category contains reviews discussing specific aspects of the item, allowing customers to navigate and process information in manageable segments rather than overwhelming them with all reviews simultaneously.
Solution Approach 2:
The patent introduces an intermediary system (the review categorization and selection mechanism) that mediates between the complete set of reviews and the customer. This intermediary automatically categorizes, ranks, and selects representative reviews, reducing the customer's processing burden while preserving access to comprehensive review information.
2Loss of information
If all reviews are displayed to customers, then the comprehensiveness is improved, but the time required to find useful information increases
Solution Approach 1:
The patent performs preliminary actions by automatically categorizing and ranking reviews before they are presented to customers. Reviews are pre-processed into categories based on item attributes and ranked within each category, so that when customers access the reviews, the most relevant information is already organized and prioritized, eliminating the need for customers to manually search through all reviews.
Solution Approach 2:
The patent applies local quality by providing different levels of review organization and presentation based on customer needs. Each category contains reviews with specific focus areas, and representative reviews are highlighted within categories, allowing customers to quickly access locally-relevant information without processing the entire review set.
3Adaptability or versatility
If diverse opinions in reviews are preserved, then the viewpoint diversity is improved, but the difficulty of extracting useful information increases
Solution Approach 1:
The patent segments diverse review opinions into distinct categories based on item attributes. Each category groups reviews with similar viewpoints or focus areas (e.g., positive comments about quality, negative comments about price). This segmentation preserves viewpoint diversity while making it easier for customers to extract useful information by allowing them to selectively explore categories relevant to their decision-making needs.
Data Source
AI summary
Disclosed are various embodiments for extracting an excerpt from a representative review of an item, such as an item available for purchase in an electronic commerce system. Attributes or categories used in reviews of an item may be identified and ranked according to consumer preference. Upon ranking the categories, an excerpt may be extracted from a review corresponding to a ranked one of the attributes or categories. The excerpt may be identified and extracted if a number of reviews for an item exceeds a threshold quantity as it may be impractical for a user to read every review written about the item.