Expert Engine is a search engine for patent attorneys to find the most appropriate people to serve as expert witnesses. At present, attorneys must rely on their own personal networks to find experts. This is inefficient and does not necessarily guarantee a strong pairing of experts with cases. Expert Engine seeks to eliminate these inefficiencies. The model currently responsible for recommending them is very simple and does not take advantage of all of the rich data that patents offer. The code here is intended to improve the algorithm so that the service can be not only faster than the traditional method of finding an expert but also guarantee the recommendation of highly qualified people.
The finished model combines the results from three measures: the original basic model with optimized features (basic_model.py with params determined by sim_anneal_model.py), predicted probabilities by naive Bayes analysis of a bag of words derived from patent contents (naive_bayes.py), and similarity of patents using SimRank (simrank.py). All three models are based on the idea that data about patents that experts have previously worked on is a good stand-in for data about the experts themselves, which is not always available.
Files contained in this repo:
The framework of Scott's original CPC-based model, with the ability to alter the parameters and aggregation of groups of CPC scores.
Combines the scores from basic_model, naive_bayes and simrank into a single predictor.
Computes the cost associated with a given model of predicting experts. The cost in this case is defined as the sum of the list indices where each "true" expert for a patent is found in the predictions for thatpatent.
Returns expert predictions based on basic multinomial naive Bayes with TF-IDF vectorizer.
Scrapes and formats relevant patent data.
Used for scraping networks of patent citations for eventual use in SimRank algorithm. Collects patent numbers of both in and out references and inserts these into SQL tables.
Subset of basic_model that uses parameters and aggregation specified in original documentation for Expert Engine.
Optimizes parameters of basic model using simulated annealing optimization.
Implements SimRank using matrix operations.
Takes data from data folders and by scraping patents and places it into appropriate SQL tables.
Intellectual Property Notice and Ownership
© 2014 Erin Burnside. All rights reserved, exclusive of U.S. government works.
This project is subject to U.S. Patent Application Number 61973202.
Scott Sherwin and Erin Burnside agree to assign (including executing any necessary formal documents) all intellectual property rights (including copyright, patent, and trademark rights) created during the scope of this project to Expert Engine upon its formation.
Neither the name Expert Engine nor the names of its contributors may be used to endorse or promote products related to this software without specific prior written permission.