PATENT CLAIM ANALYSIS

Application Number: 15945979
Application Type: Utility
Filing Date: 2018-04
Publication Date: 2019-03
Patent Classification: ["704", "002000"]

Abstract:
A sentence generating method includes: generating a corresponding word set of a source word set generated based on a source sentence; generating words by performing decoding based on feature vectors generated through encoding of the source sentence; adjusting a probability of at least one of the generated words based either one or both of the source word set and the corresponding word set; and selecting character strings from different character strings including each of the generated words based on the adjusted probability and the probability as unadjusted.

Claim (Index 13):
A sentence generating apparatus, comprising:\n a controller configured to\n generate a corresponding word set of a source word set generated based on a source sentence, \n generate words by performing decoding based on feature vectors generated through encoding of the source sentence, \n adjust a probability of at least one of the generated words based on either one or both of the source word set and the corresponding word set, and \n select character strings from different character strings including each of the generated words based on the adjusted probability and the probability as unadjusted.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 91.0
- Lexical Diversity: 2.04444
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['13813463', '15598966', '15247490', '13883758', '13114741']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2339305195986733
- 35 USC 102 Novelty (BERT): 0.4797780470418191
- Combined Prediction Score: 0.2585152723429879
- Mean Citation Score: 196.6914
- Max Citation Score: 206.37233
- Similarity Product: 167.25678329180002

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