PATENT CLAIM ANALYSIS

Application Number: 15908346
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["717", "120000"]

Abstract:
The disclosed method may include accessing features including feature information of one or more candidate target projects and of a subject project, in which the candidate target projects and the subject project are software programs. The method may include determining a similarity score between the feature information of each of the candidate target projects and the feature information of the subject project, in which a similarity score is determined for each feature of each of the candidate target projects. The method may include aggregating the similarity scores of the feature information of each feature in the candidate target projects to create an aggregate similarity score for each of the candidate target projects and generate a set of similar target projects. The method may include modifying the subject project by implementing recommended code, based on the similar target projects, in the subject project to repair a defect.

Claim (Index 17):
The non-transitory computer-readable medium of  claim 11 , wherein determining the similarity score is performed according to expressions: x 1 \u2032 = tf d \ue8a0 ( x ) \u00d7 idf \ue8a0 ( t 1 ) = k 1 x + k 1 \ue8a0 ( 1 - b + b \ue89e \ue89e l d l C ) \u00d7 log \ue89e \ue89e N + 1 n t + 0.5 ; y 1 \u2032 = tf q \ue8a0 ( y ) \u00d7 idf \ue8a0 ( t 1 ) = k 1 y + k 1 \ue8a0 ( 1 - b + b \ue89e \ue89e l d l C ) \u00d7 log \ue89e \ue89e N + 1 n t + 0.5 ; s \ue8a0 ( d f \u2192 , q f \u2192 ) = \u2211 i = 1 n \ue89e tf d \ue8a0 ( x i ) \u00d7 tf q \ue8a0 ( y i ) \u00d7 idf \ue8a0 ( t i ) 2 ; d f \u2192 = ( x 1 \u2032 , x 2 \u2032 , \u2026 \ue89e \ue89e \u2026 \ue89e , x n \u2032 ) ; and \ue89e \n \ue89e q f \u2192 = ( y 1 \u2032 , y 2 \u2032 , \u2026 \ue89e \ue89e \u2026 \ue89e , y n \u2032 ) , wherein:\n x\u2032 1  represents a BM25-based weight of a term in a document of one of the candidate target projects; \n y\u2032 1  represents a BM25-based weight of a term in a query of the subject project; \n s( ) represents a function for computing a similarity score; \n tf d (x i ) represents a smoothed term frequency of an i th  term in a document of one of the candidate target projects; \n tf q (y i ) represents a smoothed term frequency of an i th  term in a query of the subject project; \n idf(t i ) represents an inverse document frequency of an i th  term t; \n x represents a term frequency; \n y represents a term frequency; \n {right arrow over (d f )} represents a document vector; \n {right arrow over (q f )} represents a query vector; \n b represents a scaling factor; \n l d  represents a document length; \n l c  represents an average document length; \n n t  represents a number documents in the candidate target projects having a term t; \n N represents a total number of words in a dictionary; and \n \u00d7 is a scalar multiplier.

Metadata:
- Claim Count in Document: 40.0
- Percentile: 88.0
- Lexical Diversity: 2.8
- Patent Class: 717.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13479648', '15275494', '12033308', '12041629', '14219613']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4104700202851446
- 35 USC 102 Novelty (BERT): 0.5045948048435446
- Combined Prediction Score: 0.4198824987409846
- Mean Citation Score: 202.216488
- Max Citation Score: 222.40976
- Similarity Product: 160.378187124424

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