1 Amazon.co.jp *1 5 review *2 web Google web web 5 web web 5 (a) (b) (c) 3 S-PLUS S S-PLUS 1 S-PLUS S R R RMeCab *3 R term matrix S-PLUS S-PLUS *1 Ama
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2 1 Amazon.co.jp *1 5 review *2 web Google web web 5 web web 5 (a) (b) (c) 3 S-PLUS S S-PLUS 1 S-PLUS S R R RMeCab *3 R term matrix S-PLUS S-PLUS *1 Amazon.co.jp web *2 web *3 web 2
3 2 2.1 Google web Yahoo 1 3
4 1 web 5 ivedoor 3 Yahoo 2 5 ivedoor 2 Yahoo 1 5 ivedoor 3 Yahoo data.frame() 4 matrix() 4 S-PLUS 6.2J for Windows ward R ward S-PLUS mass corresp() R MASS S-PLUS R RMeCab
5 2.3 Relative Value, RV n X = (x 1, x 2, x 3,..., x n ) x i RV i = 1 i = k(1 < k < n) RV = n i=2 (x i x 1 ) 2 n (1) RV = k 1 i=1 (x i x k ) 2 + n i=k+1 (x i x k ) 2 n (2) i = n RV = n 1 i=1 (x i x n ) 2 n (3) *4 RV S-PLUS RV() RV2() *4 i = 1 k 1 1 RV() 1 RV2() RV() 5
6 Not Adjusted Adjusted y y x x 1 1 Adjusted Bubble Plot Bubble Chart evaluation 1 RV x y RV athome pina RV 6
7 RV athome mailish md pina evaluation 2 RV mailish pina RV RV athome RV 4 RV
8 3 5 comprehensive food service atmosphere food 3 4 atmosphere RV 4 5 comprehensive service RV RV RV comprehensive food service atmosphere evaluation x = 0 2 RV RV 5 7 RV
9 RV evaluation ward , 7; 8, 6, 4; 3, 2; , 7 8, 6, 4 3, ; 7, 2, 4, 5; 3, 6, 8 3 3, 5, 7; 1, 4; 6, 8; 2 9
10 5 Classification CA Classification PCA 3 Height hclust (*, "ward") 5 Classification CA Classification PCA Height sub1.txt sub7.txt sub2.txt sub4.txt sub5.txt sub3.txt sub6.txt sub8.txt sub2.txt sub3.txt sub5.txt sub7.txt sub1.txt sub4.txt sub6.txt sub8.txt hclust (*, "ward") 6 10
11 *5 *6 node, span, *5 RMeCab RMeCabFreq() *6 RMeCab collocate() 11
12 RV RV 12
13 ?? R S-PLUS 13
14 1 R Text Mining Studio S-PLUS R S S-PLUS GUI Text Mining Studio S-PLUS R S-PLUS R web 1 [1] Brian S. Everitt. An R and S-PLUS Companion to Multivariate Analysis. Springer-Verlag, R S-PLUS [2],,,,.., [3]. R., [4].., [5] Uwe Ligges. Programmieren mit R. Springer-Verlag, R [6]. R.,
15 # # OK # 1 # # x <- c(4, 1, 1, 2, 5) # # y <- RV(x) # RV <- function(x){ n <- length(x) res <- sum((x[2:n] - x[1])^2) / n res # RV() # OK # # x <- c(4, 1, 1, 2, 5) # # y <- RV2(x) # RV2 <- function(dat){ n <- length(dat) # res <- numeric(n) # n res for(i in 1:n){ if(i == 1){ # 1, num1 <- dat[i] # 1 num1 num2 <- dat[(i+1):n] # 2 n num2 res[i] <- RV(c(num1, num2)) else if(i == n){ # n, num1 <- dat[i] # n num1 num2 <- dat[1:(i-1)] # 1 n-1 num2 res[i] <- RV(c(num1, num2)) else{ # : 2 n-1, num1 <- dat[i] # i(1 > i > n) num2 <- c(dat[1:(i-1)], dat[(i+1):n]) res[i] <- RV(c(num1, num2)) 15
16 return(res) # arw.plot.df() arw.plot.mat() arw.plot2 <- function(x, y, arw=false, renew=false, pcol, ylimit=false, xlimit=false){ xy.tbl <- table(x, y) # nx <- nrow(xy.tbl) # ny <- ncol(xy.tbl) # vx <- as.numeric(rownames(xy.tbl)) # numeric vy <- as.numeric(colnames(xy.tbl)) # numeric # # renew == TRUE plot() if(renew == FALSE){ plot( c(-1, ifelse(xlimit=="true", as.numeric(readline("xlim : ")), max(x)+1)), c(-1, ifelse(ylimit=="true", as.numeric(readline("ylim : ")), max(y)+1)), xlab="evaluation", ylab="rv", type="n") abline(h=0, v=0, lty=3) # # xy.tbl cex for (i in 1:nx) { for (j in 1:ny) { if (xy.tbl[i, j] > 0) points(vx[i], vy[j], cex=xy.tbl[i, j], col=pcol) a <- cbind(x, y) a <- a[order(a[,1]), ] points(a[,1], a[,2], col=pcol, type="c") xm <- mean(x) # x ym <- mean(y) # y points(xm, ym, pch="+", cex=2, col=pcol) # (xm,ym) 16
17 # (arw.plot2() RV2() ) # 1, 2 ( ) # DF:,adj: TRUE arw.plot.df <- function(df, adj=false, legend.adj=false){ nc <- ncol(df) if(nc > 2) stop(message=" ") lab <- levels(df[, 2]) # 2 lab.n <- length(lab) # for(i in 1:lab.n){ x <- DF[DF[,2] == lab[i], ] # i x <- x[,1] # x y <- RV2(x) # RV y if(i == 1){ # adj=true arw.plot2(x, y, pcol=i, xlimit=adj, ylimit=adj) else{ # arw.plot2(x, y, pcol=i, renew=true) # legend( ifelse(legend.adj=="true", as.numeric(readline("x : ")), -1), ifelse(legend.adj=="true", as.numeric(readline("y : ")), 1), c(lab), col=1:lab.n, lwd=2) # (arw.plot2() RV2() ) # dat:,rc:1,2 # adj: arw.plot.mat <- function(dat, rc, adj=false, legend.adj=false){ nr <- nrow(dat) # nc <- ncol(dat) # # rc=1 if(rc == 1){ for(i in 1:nr){ 17
18 x <- c(dat[i, ]) # i y <- RV2(x) # RV if(i == 1){ arw.plot2(x, y, pcol=i, xlimit=adj, ylimit=adj) else{ arw.plot2(x, y, pcol=i, renew=true) # #,NULL row.name <- rownames(dat) if(is.null(row.name) == TRUE) row.name <- as.character(1:nr) legend( ifelse(legend.adj=="true", as.numeric(readline("x : ")), -1), ifelse(legend.adj=="true", as.numeric(readline("y : ")), 1), row.name, col=1:nr, lwd=2) else{ # rc=1 for(i in 1:nc){ x <- c(dat[, i]) # i y <- RV2(x) # RV if(i == 1){ arw.plot2(x, y, pcol=i, xlimit=adj, ylimit=adj) else{ arw.plot2(x, y, pcol=i, renew=true) # #,NULL col.name <- colnames(dat) if(is.null(col.name) == TRUE) col.name <- as.character(1:nc) legend( ifelse(legend.adj=="true", as.numeric(readline("x : ")), -1), ifelse(legend.adj=="true", as.numeric(readline("y : ")), 1), col.name, col=1:nc, lwd=2) 18
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