PATENT CLAIM ANALYSIS

Application Number: 15900176
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-11
Patent Classification: ["704", "009000"]

Abstract:
An artificial intelligence based method and apparatus for generating information are disclosed. The method in an embodiment includes: segmenting a to-be-processed text into characters to obtain a character sequence; determining a character vector for each character in the character sequence to generate a character vector sequence; generating a plurality of character vector subsequences by segmenting the character vector sequence based on a preset vocabulary; for each generated character vector subsequence, determining a sum of character vectors composing the character vector subsequence as a target vector, and inputting the target vector into a pre-trained first neural network to obtain a word vector corresponding to the each character vector subsequence, the first neural network used to characterize a correspondence between the target vector and the word vector; and analyzing the to-be-processed text based on the obtained word vector to generate an analysis result. This embodiment improves the adaptability of text processing.

Claim (Index 12):
The apparatus for generating information according to  claim 11 , wherein the operations further comprise:\n extracting a preset second training sample, wherein the second training sample includes a plurality of second preset words and word vectors of the second preset words in the plurality of second preset words; determining, for each of the plurality of second preset words in the second training sample, character vectors for characters composing the second preset word, to generate a character vector sequence corresponding to the second preset word; inputting the character vector sequence corresponding to each second preset character in the second training sample into the first neural network, and determining a vector output by the first neural network as an intermediate vector corresponding to the second preset character; and training and obtaining the second neural network, by using the machine learning method, and by assigning an intermediate vector sequence corresponding to the second preset word as an input, and the word vector of the second preset word in the second training sample as an output.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 88.0
- Lexical Diversity: 2.31884
- Patent Class: 704.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15900166', '15407713', '15408526', '15426727', '12707283']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2980998827566282
- 35 USC 102 Novelty (BERT): 0.4965113774353983
- Combined Prediction Score: 0.3179410322245052
- Mean Citation Score: 241.890776
- Max Citation Score: 267.73505
- Similarity Product: 217.16963522318005

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

Dataset: test