PATENT CLAIM ANALYSIS

Application Number: 16283707
Application Type: Utility
Filing Date: 2019-02
Publication Date: 2019-11
Patent Classification: ["704", "009000"]

Abstract:
Methods for determining whether two sets of words are similar are provided. In one aspect, a method includes receiving a first set of words and a second set of words, which are subsets of a vocabulary, and each of the first and second sets of words include word embeddings corresponding to each word. The method also includes determining a word membership function for each word in the vocabulary. Determining the word membership includes determining a set of similarity values, each representing the similarity between the word and a respective word in the vocabulary. The method also includes determining a membership function for the first and second sets of words based on the determined word membership functions, and determining a set-based coefficient for the similarity between the first and second sets of words based on the membership function. Systems and devices are also provided

Claim (Index 4):
The method of  claim 3  wherein the triangular conorm is the maximum triangular conorm and wherein determining the fuzzy union between the word membership functions for the respective set of words comprises determining, for each word in the vocabulary, the maximum similarity value taken from the similarity values for the word relative to each word in the set of words.

Metadata:
- Claim Count in Document: 25.0
- Percentile: 99.0
- Lexical Diversity: 2.88679
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['10573152', '16144718', '11955903', '12963161', '15478363']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2840697409218846
- 35 USC 102 Novelty (BERT): 0.4952168044436277
- Combined Prediction Score: 0.3051844472740589
- Mean Citation Score: 190.350134
- Max Citation Score: 203.3306
- Similarity Product: 132.0961315226674

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