PATENT CLAIM ANALYSIS

Application Number: 15886817
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-01
Patent Classification: ["704", "002000"]

Abstract:
A machine translation system can improve results of machine translations by employing preferred translations, such as human translated phrases. In some implementations, the machine translation system can use the preferred translations as heavily weighted training data when building a machine translation engine. In some implementations, the machine translation system can use the preferred translations as an alternate to a result that would have otherwise been produced by a machine translation engine. While it is infeasible to obtain human translations for all translation phrases, preferred translations can be used for problem phrases for which machine translation engines often produce poor translations. The machine translation system can identify problem phrases by assigning a quality score to each translation in a set of translations. The machine translation system can identify, as the problem phrases, n-grams that appear with a frequency above a frequency threshold in translations with quality scores below a threshold.

Claim (Index 13):
The computer-readable storage medium of  claim 10 , wherein the overall score for a selected n-gram, of the one or more n-grams, is based on a combination of: a frequency score indicating a frequency the selected n-gram appears in the low scoring content items, the user score corresponding to the low scoring content items the selected n-gram appears in, and a confidence factor for the selected n-gram.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 2.20548
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14967897', '14586022', '12506483', '14980654', '15672690']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2538247037407087
- 35 USC 102 Novelty (BERT): 0.5087632855248326
- Combined Prediction Score: 0.2793185619191211
- Mean Citation Score: 212.629446
- Max Citation Score: 260.83694
- Similarity Product: 188.3636833074033

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