---
title: "Reducing paper results by joining keywords"
author: "Alfonso R. Reyes"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Vignette Title}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
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.

```{r}
library(petro.One)
```


## test #1
```{r}
# provide two different set of keywords to combine as vectors
major  <- c("water injection", "water flooding")
minor  <- c("machine-learning", "intelligent")
lesser <- c("neural network", "SVM", "genetic", "algorithm")

p.df <- join_keywords(major, minor, lesser, get_papers = TRUE)
p.df
```

### test #2
```{r rows.print=20}
# 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")

p.df <- join_keywords(m, n, p, q, get_papers = TRUE)
p.df
```



## Reducing test 5.2

```{r}
# provide two different set of keywords to combine as vectors
major   <- c("waterflooding")
minor   <- c("machine-learning", "artificial intelligence")
lesser  <- c("algorithm")
another <- c("data-mining")
more    <- c("data-driven")

p.df <- join_keywords(major, minor, lesser, another, more, get_papers = TRUE)
p.df
```
