最近我在Rstudio中使用协同过滤构建了一个音乐推荐系统。我在使用余弦相似度函数时遇到了一些问题，系统提示“下标超出范围”的错误，无法计算我想要的矩阵。

我参考了这个网站上的余弦相似度方法：https://bgstieber.github.io/post/recommending-songs-using-cosine-similarity-in-r/

我尝试修复脚本，但显然输出仍然不起作用。

##cosinesim-crossprodcosine_sim <- function(a,b) {crossprod(a,b)/sqrt(crossprod(a)*crossprod(b))}##User dataplay_data <- "https://static.turi.com/datasets/millionsong/10000.txt" %>%  read_tsv(col_names = c('user', 'song_id', 'plays'))##Song datasong_data <- read_csv("D:/3rd Term/DataAnalysis/dataSet/song_data.csv") %>%  distinct(song_id, title, artist_name)##Groupedall_data <- play_data %>%  group_by(user, song_id) %>%  summarise(plays = sum(plays, na.rm = TRUE)) %>%  inner_join(song_data)top_1k_songs <- all_data %>%  group_by(song_id, title, artist_name) %>%  summarise(sum_plays = sum(plays)) %>%  ungroup() %>%  top_n(1000, sum_plays) %>%   distinct(song_id)all_data_top_1k <- all_data %>%  inner_join(top_1k_songs)top_1k_wide <- all_data_top_1k %>%  ungroup() %>%  distinct(user, song_id, plays) %>%  spread(song_id, plays, fill = 0)ratings <- as.matrix(top_1k_wide[,-1])##Functioncalc_cos_sim <- function(song_code = top_1k_songs,                          rating_mat = ratings,                         songs = song_data,                         return_n = 5) {  song_col_index <- which(colnames(ratings)== song_code) %>%  cos_sims <- apply(rating_mat, 2,FUN = function(y)                       cosine_sim(rating_mat[,song_col_index], y))##output  data_frame(song_id = names(cos_sims), cos_sim = cos_sims) %>%    filter(song_id != song_code) %>% # remove self reference    inner_join(songs) %>%    arrange(desc(cos_sim)) %>%    top_n(return_n, cos_sim) %>%    select(song_id, title, artist_name, cos_sim)}

我期望使用以下脚本时：

shots <- 'SOJYBJZ12AB01801D0'knitr::kable(calc_cos_sim(shots))

输出将是一个包含5首歌曲的数据框。

回答：

这一行的末尾有一个看起来像打字错误的管道符：

song_col_index <- which(colnames(ratings)== song_code) %>%

将其替换为：

song_col_index <- which(colnames(ratings)== song_code)