patent recommendation system
TRANSCRIPT
Patent RecommenderKarthik Chepudira, Jason Lott, Dhaval Bhatt, Prabhakar Gundugola
[email protected], [email protected], [email protected], [email protected]
Patent Research is Not Easy
Identifying the most pertinent patents in a list of thousands can be tedious and difficult. - IPWatchDog, Aug 2016
Why patent research matters?
WTF
Patents & Inventors
Patent Research• Information retrieval in patents• Beyond keyword search
Go Beyond Keywords
• Strategic Research tool
Improve Efficiencies
Patent Similarity
What if your keyword doesn’t get Patent 8 as a hit?
If Patent 4 & 5 are relevant, why not look at Patent 8?
Patent 1
Patent 8
Patent 4
Patent 5Patent 6
Patent 3
Patent 2
Patent 7
Patent Structure/Fields
••••••••••••••••••••••
Similarity Measures
Latent Dirichlet Allocation (LDA):
● “The basic idea is that documents are represented as random mixtures over latent topics, where each topic is characterized by a distribution over words.” (Blei, Ng, & Jordan)
TF-IDF:
tf-idft,d = tft,d x idft
• High when term occurs often in few documents
• Lowest when it occurs in all documents (think stop words)
Similarity measure with LDA Topic modeling
Patent Text Fields Analysis
Unique Recommended Patents - TFIDF
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Key Takeaways
Similarity Metrics
Comparing Patents From Two Similarity Metrics
Green - TF-IDF BasedRed - LDAYellow - Overlap
Standard
Top 5 Results Change in Rank
LM Dirichlet
ResultsInput Data Patent Recommender
Patent
SYSTEMS AND/OR METHODS FOR STRUCTURING BIG
DATA BASED UPON USER-SUBMITTED DATA ANALYZING PROGRAMS
MODELING AND SIMULATION OF INFRASTRUCTURE
ARCHITECTURE FOR BIG DATA
REGIONAL BIG DATA IN PROCESS CONTROL SYSTEMS
METHOD FOR MANAGING IoT DEVICES AND ANALYZING SERVICE OF BIG DATA
JOINING DATA ACROSS A PARALLEL DATABASE AND A DISTRIBUTED PROCESSING SYSTEM
Systems and Methods for Auto-Scaling a Big Data System
DATA PROCESSING APPARATUS AND METHOD OF PROCESSING DATA
STREAMING DATA FOR ANALYTICS IN PROCESS CONTROL SYSTEMS
Configurable Machine Learning Method Selection and Parameter Optimization System and Method
Patent Recommender
Patents Score
1.9256938
1.6159785
1.0616564
1.0573796
0.85843694
0.85230005
0.82034045
UI Testing & Iteration
Demo
Testimonial
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Week 6-7
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Week 8-10 Week 11-13
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Week 14
Capstone DemoIn case the live demo doesn’t work out
Keyword searchSearch Phrase: Polycrystalline diamond tungsten carbide leachClick SHOW MORE => Click CREATE NEW PROFILE
Tune ProfileRemove patent #2 & #8 | Change Scores | RECOMMEND PATENTS
RecommendationsThe 3rd result is what made Trent say “Oh, that interesting!”
Patent LinkWe wanted to allow the user to review the patents we recommend.
Clicking on the link was natural and required no explanation.
EvaluationUser Rating of Recommendations
Future Work
Future Work● Future: User click on show more most of the time, start out with a larger list● “patent continuations” we want to incorporate a way to deal with these. Don’t
want to have continuations showing up in patent profiles or dominating the recommendations
● Future: Adding patents to profile from here. Would allow us to look at precision as an evaluation of the recommendations.
● Future: Click on score to see indication why (keywords, topic,..) to allow user to evaluate recommendation without reading. Allows to generate new keywords as well as filter out false positives.
The Big PictureWe see this page becoming a sub-page to a user profile. The profile could contain many collections, and when you login, you get to see prompts for looking at recommendations on established collections again. That was one of the comments we got, that he sees this as a stepping stone to that.