Nothing
## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ------------------------------------------------------------------------
library(petro.One)
## ---- 5-keywords---------------------------------------------------------
# provide two different set of keywords to combine as vectors
major <- c("water injection", "water flooding")
minor <- c("machine-learning", "artificial intelligence")
lesser <- c("neural networks")
result_object <- join_keywords(major, minor, lesser, get_papers = TRUE)
result_object
## ------------------------------------------------------------------------
# save findings
# save the three objects as one
papers <- result_object
wat_inj_ml_1 <- petro.One:::as_named_list(major, minor, lesser, papers)
save(wat_inj_ml_1, file = paste0("wat_inj_ml_1", ".rda"))
# load previous save
load(file = paste0("wat_inj_ml_1", ".rda"))
papers <- wat_inj_ml_1$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)
## ------------------------------------------------------------------------
# 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$papers
## ---- 6-keywords---------------------------------------------------------
# provide two different set of keywords to combine as vectors
maj <- c("waterflooding")
min <- c("machine-learning", "artificial intelligence")
les <- c("algorithm")
anr <- c("data-mining", "data-driven")
paper_results_5 <- run_papers_search(maj, min, les, anr,
get_papers = TRUE, # return with papers
verbose = FALSE, # show progress
len_keywords = 4, # naming the data file
allow_duplicates = FALSE) # by paper title and id
paper_results_5$keywords
## ------------------------------------------------------------------------
paper_results_5$search_keywords
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