In f0nzie/petro.One: Statistics and Text Mining for Oil and Gas Papers from OnePetro Metadata

knitr::opts_chunk$set(echo = TRUE, 
                      comment = NA, 
                      error = TRUE, 
                      warning = FALSE, 
                      message = FALSE, 
                      fig.align = 'center')

Retrieve papers from OnePetro

well +production + production engineering + machine learning

library(petro.One)
library(dplyr)

# provide two different set of keywords to combine as vectors
major   <- c("production", "production engineering")
minor   <- c("machine-learning", "machine learning")


paper_results <- run_papers_search(major, minor, get_papers = TRUE, 
                                   verbose = FALSE, len_keywords = 4)

(papers <- paper_results$papers)

# No need

# # eliminate duplicates by paper_id and paper title
# papers <- papers %>% 
#     distinct(paper_id, book_title, .keep_all = TRUE) %>% 
#     print

what papers have machine learning in the title

papers %>%
    # machine learning OR machine-learning
    filter(grepl(pattern = "machine[-\\s]learning", 
                 x = book_title, ignore.case = TRUE, perl = TRUE))

what papers have artificial intelligence in the title

papers %>%
    # machine learning OR machine-learning
    filter(grepl(pattern = "artificial[-\\s]intelligence", 
                 x = book_title, ignore.case = TRUE, perl = TRUE))

f0nzie/petro.One documentation built on May 29, 2019, 12:05 a.m.