# US 2026/0073418 A1 · Natural language model based real estate trend predictions

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2026/0073418 A1
- Document ID: US20260073418A1
- Status: Published application
- Kind: A1
- Application number: 19/325,290
- Filed: 2025-09-10
- Published: 2026-03-12
- Earliest claimed: 2024-09-11
- Assignees: CoreLogic Solutions, LLC
- Applicants: CoreLogic Solutions, LLC
- Inventors: Matthew Delventhal; Kien Trong Trinh; Uyen Hoang; Bin He; David Stiff
- Web page: https://patentgrep.com/patent/US20260073418A1

## CPC

- G06F 40/30: Semantic analysis
- G06Q 30/0206: {Price or cost determination based on market factors}
- G06F 40/20: Natural language analysis (semantic analysis of natural language G06F40/30)
- G06F 40/284: Lexical analysis, e.g. tokenisation or collocates
- G06Q 30/0201: Market modelling; Market analysis; Collecting market data
- G06Q 30/0202: Market predictions or forecasting for commercial activities
- G06Q 50/16: Real estate
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

Systems and methods for providing real estate trends and other insights based on a natural language process of text data, including various news sources, to a specified market (e.g., national, local). In some embodiments, the real estate prediction system performs semantic-based analysis to determine a sentiment associated with a source. For example, the real estate prediction system can access an embedding system to generate embeddings for words and phrases contained within a source. These embeddings can be input to an LLM for determination of a general sentiment of the source, or used directly in an LLM. The real estate prediction system perform additional semantic analysis, such as word counting, to classify and organize the content of sources. Based on the generated sentiments, the real estate prediction system can generate predictions, estimations, and other insights relating to the sources.

## Claims

### Claim 1

A system, comprising:
a computer-readable storage medium storing program instructions; and
one or more processors, wherein the program instructions, when executed by the one or more processors, cause the one or more processors to:
access a source;
determine, based on the source, a plurality of word counts, wherein each word count comprises an occurrence frequency of a word and a word sentiment associated with the word;
determine, based on the source, a plurality of word embeddings within an embedding space, wherein locations of the plurality of word embeddings within the embedding space indicate a similarity between each word of the source;
input the plurality of word embeddings and the plurality of word counts into a natural language processing model, the natural language processing model to output a source sentiment associated with the source;
determine a confidence score associated with the source sentiment, wherein the confidence score indicates a correlation between the source sentiment and the source; and
determine a trend prediction based on the source sentiment.

### Claim 2 (depends on 1)

The system of claim 1, wherein the source includes at least one of an article, a newspaper article, a blog article, an online publication, a print publication, a magazine, an editorial, a review, a brochure, an opinion, a press release, a post, a photo, a video, an audio file, a diagram, a column, or a feature.

### Claim 3 (depends on 1)

The system of claim 1, wherein the trend prediction is one of a predicted property cost estimate, rental estimate, mortgage rate, inventory, demand, or a statistic.

### Claim 4 (depends on 1)

The system of claim 1, wherein the program instructions, when executed, further cause the one or more processors to:
determine, using a forecasting engine a baseline property value for a property, wherein the property;
receive a request for a property value estimation for the property;
access the baseline property value, weekly property data, and the source sentiment;
determine the property value estimation, wherein determination of the property value estimation comprises:
input, into a forecasting engine, the baseline property value, the weekly property data and the source sentiment; and
adjust the baseline property value based on the weekly property data and the source sentiment to determine the property value estimation; and
display the property value estimation.

### Claim 5 (depends on 4)

The system of claim 4, wherein the program instructions further cause the system to store the property value estimation in a results cache.

### Claim 6 (depends on 4)

The system of claim 4, wherein the program instructions, when executed, further cause the one or more processors to generate, by the forecasting engine, an interpolation of the property value estimation using cubic spline interpolation.

### Claim 7 (depends on 1)

The system of claim 1, wherein the program instructions, when executed, further cause the one or more processors to:
generate a sentiment score plot based on the source sentiment; and
display the sentiment score plot and the trend prediction on a graphical user interface.

### Claim 8

A method, comprising:
accessing a source;
determining, based on the source, a plurality of word counts, wherein each word count comprises an occurrence frequency of a word and a word sentiment associated with the word;
determining, based on the source, a plurality of word embeddings within an embedding space, wherein locations of the plurality of word embeddings within the embedding space indicate a similarity between each word of the source;
inputting the plurality of word embeddings and the plurality of word counts into a natural language processing model, the natural language processing model to output a source sentiment associated with the source;
determining a confidence score associated with the source sentiment, wherein the confidence score indicates a correlation between the source sentiment and the source; and
determining a trend prediction based on the source sentiment.

### Claim 9 (depends on 8)

The method of claim 8, wherein the source includes at least one of an article, a newspaper article, a blog article, an online publication, a print publication, a magazine, an editorial, a review, a brochure, an opinion, a press release, a post, a photo, a video, an audio file, a diagram, a column, or a feature.

### Claim 10 (depends on 8)

The method of claim 8, wherein the trend prediction is one of a predicted property cost estimate, rental estimate, mortgage rate, inventory, demand, or a statistic.

### Claim 11 (depends on 8)

The method of claim 8, further comprising:
determining, using a forecasting engine a baseline property value for a property, wherein the property;
receiving a request for a property value estimation for the property;
accessing the baseline property value, weekly property data, and the source sentiment;
determining the property value estimation, wherein determination of the property value estimation comprises:
inputting, into the forecasting engine, the baseline property value, the weekly property data and the source sentiment; and
adjusting the baseline property value based on the weekly property data and the source sentiment to determine the property value estimation; and
displaying the property value estimation.

### Claim 12 (depends on 11)

The method of claim 11, further comprising storing the property value estimation in a results cache.

### Claim 13 (depends on 11)

The method of claim 11, further comprising generating, by the forecasting engine, an interpolation of the property value estimation using cubic spline interpolation.

### Claim 14 (depends on 8)

The method of claim 8, further comprising:
generating a sentiment score plot based on the source sentiment; and
displaying the sentiment score plot and the trend prediction on a graphical user interface.

### Claim 15

A non-transitory computer-readable medium storing specific computer-executable instructions that, when executed by a processor of a computing device, cause the computing device to:
access a source;
determine, based on the source, a plurality of word counts, wherein each word count comprises an occurrence frequency of a word and a word sentiment associated with the word;
determine, based on the source, a plurality of word embeddings within an embedding space, wherein locations of the plurality of word embeddings within the embedding space indicate a similarity between each word of the source;
input the plurality of word embeddings and the plurality of word counts into a natural language processing model, the natural language processing model to output a source sentiment associated with the source;
determine a confidence score associated with the source sentiment, wherein the confidence score indicates a correlation between the source sentiment and the source; and
determine a trend prediction based on the source sentiment.

### Claim 16 (depends on 15)

The non-transitory computer-readable medium of claim 15, wherein the source includes at least one of an article, a newspaper article, a blog article, an online publication, a print publication, a magazine, an editorial, a review, a brochure, an opinion, a press release, a post, a photo, a video, an audio file, a diagram, a column, or a feature.

### Claim 17 (depends on 15)

The non-transitory computer-readable medium of claim 15, wherein the trend prediction is one of a predicted property cost estimate, rental estimate, mortgage rate, inventory, demand, or a statistic.

### Claim 18 (depends on 15)

The non-transitory computer-readable medium of claim 15, wherein the computer-executable instructions, when executed, further cause the computing device to:
determine, using a forecasting engine a baseline property value for a property, wherein the property;
receive a request for a property value estimation for the property;
access the baseline property value, weekly property data, and the source sentiment;
determine the property value estimation, wherein determination of the property value estimation comprises:
input, into a forecasting engine, the baseline property value, the weekly property data and the source sentiment; and
adjust the baseline property value based on the weekly property data and the source sentiment to determine the property value estimation; and
display the property value estimation.

### Claim 19 (depends on 18)

The non-transitory computer-readable medium of claim 18, wherein the computer-executable instructions, when executed, further cause the computing device to store the property value estimation in a results cache.

### Claim 20 (depends on 18)

The non-transitory computer-readable medium of claim 18, wherein the computer-executable instructions, when executed, further cause the computing device to generate, by the forecasting engine, an interpolation of the property value estimation using cubic spline interpolation.