PATENT CLAIM ANALYSIS

Application Number: 16396581
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-10
Patent Classification: ["705", "313000"]

Abstract:
Described are applications and methods to detect a real estate transfer event and validate the detected event from a data set ingested from a plurality of unique external data sources by identifying an initial candidate, determining the probability that the improper real estate transfer event has taken place, and validating the probability of the improper real estate event.

Claim (Index 26):
A computer implemented method to detect an improper real estate transfer event, the method comprising:\n a) defining, by a parameter setting module, a data set to be evaluated; b) detecting, by a plurality of data ingestion interfaces, one or more real estate transfer indicia within the data set, wherein each interface connects to a unique external data source, and wherein each interface performs a data mining task process to its data source to detect the one or more real estate transfer indicia; c) identifying an initial candidate by applying a machine learning algorithm to the real estate transfer indicia within the data set; d) calculating, by an improper real estate transfer probability calculation module, a probability that the improper real estate transfer event has taken place at the initial candidate; e) accepting, by a validation module, verified data regarding the real estate transfer event; and f) feeding back the verified data to the improper real estate transfer probability calculation module to improve its calculation over time.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 100.0
- Lexical Diversity: 1.5641
- Patent Class: 705.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['16000750', '14923663', '16135099', '14030997', '15820260']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.0878124193712658
- 35 USC 102 Novelty (BERT): 0.4951285853266362
- Combined Prediction Score: 0.1285440359668028
- Mean Citation Score: 170.02143600000005
- Max Citation Score: 195.04955
- Similarity Product: 130.8723428576112

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 0

Dataset: test