PATENT CLAIM ANALYSIS

Application Number: 15888385
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-06
Patent Classification: ["704", "009000"]

Abstract:
Topics are determined for short text messages using an unsupervised topic model. In a training corpus created from a number of short text messages, a vocabulary of words is identified, and for each word a distributed vector representation is obtained by processing windows of the corpus having a fixed length. The corpus is modeled as a Gaussian mixture model in which Gaussian components represent topics. To determine a topic of a sample short text message, a posterior distribution over the corpus topics is obtained using the Gaussian mixture model.

Claim (Index 20):
A tangible computer-readable medium having stored thereon computer readable instructions for determining topics of short text messages, wherein execution of the computer readable instructions by a processor causes the processor to perform operations comprising:\n obtaining distributed vector representations of words in a vocabulary identified in a corpus comprising a plurality of training short text messages, the distributed vector representations being obtained by processing context windows of the corpus using a continuous bag of words model; estimating a plurality of Gaussian components of a Gaussian mixture model of the corpus using the distributed vector representations, the Gaussian components representing corpus topics; receiving a sample short text message comprising a subset of the words in the vocabulary; and determining a topic of the sample short text message based on a posterior distribution over the corpus topics for the sample short text message, the posterior distribution obtained using the Gaussian mixture model.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 88.0
- Lexical Diversity: 1.68421
- Patent Class: 704.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['14519427', '15401446', '13433111', '12907219', '13364535']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2794400022475042
- 35 USC 102 Novelty (BERT): 0.6037875906388303
- Combined Prediction Score: 0.3118747610866368
- Mean Citation Score: 355.57666200000006
- Max Citation Score: 533.1731
- Similarity Product: 496.0738571008682

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

Dataset: test