PATENT CLAIM ANALYSIS

Application Number: 15902474
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-08
Patent Classification: ["701", "031900"]

Abstract:
System and method for early detection of vehicle parts failure are disclosed. The method includes identifying discriminative rules from unstructured and structured data corresponding to subsystems of a vehicle. Causal parts categories are mapped to the subsystems based on the discriminative rules to obtain a plurality of causal part-subsystem pairs. The causal part categories are representative of vehicle parts responsible for failure of corresponding subsystems. Scores are assigned to the causal part-subsystem pairs based on an occurrence of causal part categories to a corresponding subsystem within a source. An emerging issue score is computed based on the scores, a corresponding weightage associated with the sources of the causal part category, and an extent of coverage of the each causal part in each of the plurality of causal part-subsystem pairs. The emerging issue score is compared with the threshold vehicle part failure score to identify causal part categories associated with vehicle parts failure.

Claim (Index 13):
The non-transitory computer-readable medium having embodied thereon a computer program for executing, a computer-implemented method for early detection of vehicle parts failure for a vehicle having a plurality of subsystems comprising:\n identifying, via one or more hardware processors, a plurality of discriminative rules from an unstructured data and a structured data corresponding to the plurality of subsystems, the unstructured data and a structured data derived from a plurality of sources;\n mapping, via the one or more hardware processors, and based on the plurality of discriminative rules, a plurality of causal part categories associated with the structured data and the unstructured data with the plurality of subsystems to obtain a plurality of causal part-subsystem pairs, a causal part-subsystem pair comprising mapping of a causal part category with a corresponding subsystem, and wherein the plurality of causal part categories are representative of vehicle parts responsible for failure of a corresponding subsystem of the plurality of subsystems; \n assigning, via the one or more hardware processors, a score to each of the plurality of causal part-subsystem pairs based on the pattern of occurrence of causal part categories corresponding to a subsystem of the plurality of subsystems within a source of the plurality of sources; \n computing, via the one or more hardware processors, and corresponding to each causal part category of the plurality of causal part categories, an emerging issue score based on the score assigned to each of the plurality of causal part-subsystem pairs and a corresponding weightage associated with a source of the plurality of sources of the causal part category, and an extent of coverage of the each causal part in each of the plurality of causal part-subsystem pairs; and \n identifying, via the one or more hardware processors, one or more causal part categories associated with vehicle parts failure based on a comparison of the emerging issue score with a threshold vehicle part failure score.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 88.0
- Lexical Diversity: 2.40299
- Patent Class: 701.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15057882', '13782914', '13677927', '14687748', '14815112']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4089476937356016
- 35 USC 102 Novelty (BERT): 0.454187789780864
- Combined Prediction Score: 0.4134717033401278
- Mean Citation Score: 144.69352200000003
- Max Citation Score: 156.08485
- Similarity Product: 124.80317683859468

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

Dataset: test