PATENT CLAIM ANALYSIS

Application Number: 16396454
Application Type: Utility
Filing Date: 2019-04
Publication Date: 2019-10
Patent Classification: ["707", "602000"]

Abstract:
The present invention extends to methods, systems, and computer program products for normalizing ingested signals. In general, different types of raw signals including source data in different pluralities of data dimensions and including other characteristics are ingested. Per raw signal, a transdimensionality transform is applied to recode and normalize the source data into a normalized signal that includes normalized data in a common reduced plurality of dimensions including a time dimension, a location dimension, and a context dimension. Normalization can include inferring signal annotations from the source data and using the annotations and/or the other characteristics to derive time, location, and context dimensions. Derivation can include computing a probability of a real-world event and including the probability in the context dimension. An real-world event is detection from the normalized data in the time, location, and context dimensions and an entity is notified of the real-world event.

Claim (Index 4):
The method of  claim 3 , wherein ingesting a raw signal comprises ingesting the raw signal from a social media network source; and\n wherein ingesting another raw signal comprises ingesting the other raw signal from a source other than the social media network source.

Metadata:
- Claim Count in Document: 27.0
- Percentile: 100.0
- Lexical Diversity: 2.25
- Patent Class: 707.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16038537', '16106436', '16285031', '16106530', '16394620']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.222070419559128
- 35 USC 102 Novelty (BERT): 0.5356618466450993
- Combined Prediction Score: 0.2534295622677252
- Mean Citation Score: 288.04977599999995
- Max Citation Score: 363.92764
- Similarity Product: 223.67196757760289

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

Dataset: test