PATENT CLAIM ANALYSIS

Application Number: 16077007
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-01
Patent Classification: ["725", "012000"]

Abstract:
A system and method for providing viewership measurement for a digital media asset hosted at a particular location has been disclosed. The system employs a machine learning process to receive classified sensor data corresponding to viewership of a digital media asset at a particular location from a plurality of sources to generate trained data. The trained data is utilized by the system along with limited sensor data to provide viewership measurement of a target digital media asset whose audience is unknown.

Claim (Index 12):
The method as claimed in  claim 11 , wherein the step of classifying the fetched information into categories includes:\n a. normalizing the fetched information by using linear modelling techniques; b. classifying the fetched sensor data into categories including demographics, user migration, user interests and dwell time, wherein demographics includes gender, age group, language, migration, income details, race and religion and ethnicity c. calculating a weighted average of the information fetched from each of the sensors; and d. applying isotonic regression technique on the weighted average of information fetched from each of the sensors to consolidate the information fetched from all the sensors.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 96.0
- Lexical Diversity: 1.71429
- Patent Class: 725.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['12749376', '12386655', '15147308', '13998392', '11818485']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4426207813032359
- 35 USC 102 Novelty (BERT): 0.4808401696644572
- Combined Prediction Score: 0.446442720139358
- Mean Citation Score: 175.208928
- Max Citation Score: 187.69699
- Similarity Product: 138.95628818556722

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