AI Property Listing Generation via Image Embedding
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Solution Overview
Problem
The current manual process of creating real estate listings is time-consuming, prone to errors, and often non-compliant with industry regulations, leading to ineffective and unappealing listings that may violate ADA and MLS rules due to missing tags and incomplete information.
Innovation Solution
An automated system that encodes input images and videos to generate image embeddings, decodes them to produce property data, and uses a generative machine learning model to create property descriptions, which are then incorporated into listings, ensuring compliance and accuracy through a property listing apparatus with features like layout generation and buyer/seller recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual process is used to create property listings, then flexibility and human judgment are maintained, but time consumption increases and error compliance decreases
Solution Approach 1:
The system enables automated self-service generation of property listings by processing images and videos through encoder-decoder models to automatically extract and populate property data fields, eliminating the need for manual data entry while ensuring compliance through automated validation rules
Solution Approach 2:
The patent replaces the mechanical manual process of listing creation with an automated machine learning system that uses encoder-decoder models to process media inputs and generate structured property data, substituting human labor with computational processes
2Productivity
If manual process is used to create property listings, then human oversight is maintained, but productivity decreases and error rates increase
Solution Approach 1:
The system incorporates automated feedback mechanisms where the encoder-decoder model processes property media and generates listings that are validated against compliance rules, with the ability to iterate and correct errors automatically, ensuring high accuracy while maintaining rapid generation speeds
Solution Approach 2:
The automated system performs self-validation and self-correction of listing data through integrated compliance checking, eliminating the need for manual oversight while maintaining or improving accuracy through automated error detection and correction
3Reliability
If automated system is used to generate listings, then efficiency and compliance are improved, but system complexity increases
Solution Approach 1:
The system is segmented into distinct functional modules: encoder model for processing media inputs, decoder model for generating structured data, and compliance validation module for ensuring regulatory adherence. This modular architecture manages complexity by separating concerns while maintaining integrated functionality
Data Source
AI summary
A method, apparatus, non-transitory computer readable medium, apparatus, and system for generating real property listings includes obtaining an image of a real property; performing, using an encoder of an image processing network, a convolution process on the image to obtain an image embedding representing features of the image; decoding, using a decoder of the image processing network, the image embedding to obtain property data for the real property; and generating, using a language generation model, a description of the real property based on the image and the property data. Embodiments are further configured to generate a listing of the property by mapping the extracted information from the property data to fields in a listing. Embodiments may then provide the listing on a public access layer of a distributed computer network or a private access layer of a distributed computer network.