PATENT CLAIM ANALYSIS

Application Number: 16055336
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-02
Patent Classification: ["706", "012000"]

Abstract:
A computing device determines a bandwidth parameter value for outlier detection or data classification. A mean pairwise distance value is computed between observation vectors. A tolerance value is computed based on a number of observation vectors. A scaling factor value is computed based on a number of observation vectors and the tolerance value. A Gaussian bandwidth parameter value is computed using the mean pairwise distance value and the scaling factor value. An optimal value of an objective function is computed that includes a Gaussian kernel function that uses the computed Gaussian bandwidth parameter value. The objective function defines a support vector data description model using the observation vectors to define a set of support vectors. The Gaussian bandwidth parameter value and the set of support vectors are output for determining if a new observation vector is an outlier or for classifying the new observation vector.

Claim (Index 26):
The non-transitory computer-readable medium of  claim 25 , wherein, after (f) is performed for each class of the defined plurality of classes, the computer-readable instructions further cause the computing device to:\n receive the new observation vector; select a class from the defined plurality of classes; (g) select the SVDD model for the unique class indicator associated with the selected class; (h) compute a distance value using the selected SVDD model and the received new observation vector; (i) determine if the received new observation vector is within a radius of the selected SVDD model using the computed distance value; and (j) store an indicator of the determination and the computed distance value; and repeat (g) to (j) with each remaining class of the defined plurality of classes as the selected class; when the received new observation vector is determined to be in a single class of the defined plurality of classes based on the stored indicator, assign the received new observation vector to the single class; and when the received new observation vector is determined to not be in a single class of the defined plurality of classes based on the stored indicator, assign the received new observation vector to a class using arg \ue89e { min m = 1 , 2 , \u2026 , M \ue89e ( dist m \ue8a0 ( z ) / R m ) } , where z is the received new observation vector, M is a number of the plurality of classes, dist m (z) is the stored, computed distance value for class m, and R m  is the radius of the selected SVDD model for class m.

Metadata:
- Claim Count in Document: 81.0
- Percentile: 96.0
- Lexical Diversity: 2.63793
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15583067', '15185277', '15390236', '15096552', '15335530']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4826378576377416
- 35 USC 102 Novelty (BERT): 0.5445972479183286
- Combined Prediction Score: 0.4888337966658003
- Mean Citation Score: 387.070814
- Max Citation Score: 424.97754
- Similarity Product: 298.1176908004153

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