PATENT CLAIM ANALYSIS

Application Number: 15889168
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["704", "009000"]

Abstract:
Techniques for improving machine learning and text classification are described. The described techniques include improved processes for collecting training data to train a machine classifier. Some data sets are very large but contain only a small number of positive or negative training examples. The described text classification system obtains training examples by intelligently identifying documents that are likely to present or identify positive or negative training examples. The text classification system employs these techniques to train a classifier to categorize patent claims according some legal rule, such as subject-matter eligibility under 35 U.S.C. 101.

Claim (Index 18):
The system of  claim 16 , wherein the generating a set of patent eligible claims includes:\n obtaining claims from patents issued from the patent applications that do not include subject-matter rejections, wherein claims from patent application publications from the patent applications that do not include subject-matter rejections are not used for training the first machine learning model when the patent application has not issued into a patent; and storing the obtained claims in association with an eligibility indicator.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 1.55385
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13000025', '12658165', '13632943', '13310510', '14630751']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2559600654665123
- 35 USC 102 Novelty (BERT): 0.4737664179865137
- Combined Prediction Score: 0.2777407007185124
- Mean Citation Score: 118.17263
- Max Citation Score: 129.53055
- Similarity Product: 87.80912482661606

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

Dataset: test