Page rank implementation: http://www.cs.princeton.edu/~chazelle/courses/BIB/pagerank.htm

PageRank.kt

class PageRank(val connections: Map<String, List<String>>) {

    private val reversed: Map<String, List<String>> = connections
                    .flatMap { (k, v) -> v.map { it to k } }
                    .groupBy { it.first }
                    .mapValues { (_, v) -> v.map { it.second } }

    private var pageRank: Map<String, Double> = connections.mapValues { (_, _) -> 0.0 }

    private fun partialSum(point: String): Double {
        return (pageRank[point] ?: 0.0) / (connections[point].orEmpty().size)
    }

    private fun newPageRank(point: String, d: Double = 0.85): Double {
        return 1 - d + d * reversed[point].orEmpty().map { partialSum(it) }.sum()
    }

    fun calculate(iterations: Int = 50): Map<String, Double> {
        (1..iterations).forEach { pageRank = pageRank.mapValues { (k, v) ->  newPageRank(k)} }
        return pageRank
    }
}


fun main(args: Array<String>) {
    val connections: Map<String, List<String>> = mapOf(
            "Home" to listOf("About", "Product", "More"),
            "About" to listOf("Home"),
            "Product" to listOf("Home"),
            "More" to listOf("Home")
    )
    val pr = PageRank(connections).calculate()
    println(pr)

}