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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
This is a demonstration on how the number of papers can be reduced using additional keywords to control the number of results returned.
library(petro.One)
We start with these keywords: water injection water flooding machine-learning artificial intelligence neural networks
# provide two different set of keywords to combine as vectors major <- c("water injection", "water flooding") minor <- c("machine-learning", "artificial intelligence") lesser <- c("neural networks") result_object <- join_keywords(major, minor, lesser, get_papers = TRUE) result_object
# save findings # save the three objects as one papers <- result_object wat_inj_ml_1 <- petro.One:::as_named_list(major, minor, lesser, papers) save(wat_inj_ml_1, file = paste0("wat_inj_ml_1", ".rda")) # load previous save load(file = paste0("wat_inj_ml_1", ".rda")) papers <- wat_inj_ml_1$papers papers
paper_results <- run_papers_search(major, minor, lesser, get_papers = TRUE, # return with papers verbose = FALSE, # show progress len_keywords = 4, # naming the data file allow_duplicates = FALSE) # by paper title and id
names(paper_results)
Then, we increase the number of keywords:
water injection water flooding machine-learning machine learning intelligent neural network SVM genetic algorithm
# provide two different set of keywords to combine as vectors m <- c("water injection", "water flooding") n <- c("machine-learning", "machine learning", "intelligent") p <- c("neural network", "SVM", "genetic") q <- c("algorithm") paper_results_9 <- run_papers_search(m, n, p, q, get_papers = TRUE, # return with papers verbose = FALSE, # show progress len_keywords = 4, # naming the data file allow_duplicates = FALSE) # by paper title and id paper_results_9$papers
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