PATENT CLAIM ANALYSIS

Application Number: 15941687
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2018-10
Patent Classification: ["700", "276000"]

Abstract:
An apparatus and a method for a data learning server is provided. The apparatus of the disclosure includes a communicator configured to communicate with an external device, at least one processor configured to acquire a set temperature set in an air conditioner and a current temperature of the air conditioner at the time of setting the temperature via the communicator, and a generate or renew a learning model using the set temperature and the current temperature, and a storage configured to store the generated or renewed learning model to provide a recommended temperature to be set in the air conditioner as a result of generating or renewing the learning model. For example, the data learning server of the disclosure may generate a learned learning model to provide a recommended temperature using a neural network algorithm, a deep learning algorithm, a linear regression algorithm, or the like as an artificial intelligence algorithm.

Claim (Index 21):
The method as claimed in  claim 16 ,\n wherein the generating or renewing the learning model comprises generating or renewing a plurality of learning models for each operation mode of the air conditioner, and wherein the storing the learning model comprises storing the plurality of learning models.

Metadata:
- Claim Count in Document: 80.0
- Percentile: 90.0
- Lexical Diversity: 2.33333
- Patent Class: 700.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12315276', '12069579', '15848473', '15803051', '14326663']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3775088498409439
- 35 USC 102 Novelty (BERT): 0.5064776500183111
- Combined Prediction Score: 0.3904057298586806
- Mean Citation Score: 167.46480200000005
- Max Citation Score: 182.14
- Similarity Product: 100.64061344981192

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

Dataset: test