1. Trace file ：200 users, 4772 tracks,
each track has 4 attributes (aritst, album, track name, genre)
2. First experiment : content-based recommendation
a. Each user has 40 tracks and queries 10 tracks
b. Users exchange profiles when constructing neighborhood
c. When a user successfully queries one file from the other user, they exchange profiles
d. When a user receives other's queries, it recommends some tracks similar to the query file
e. Definition of similar tracks : more than two attributes are the same
3. Results:
There are totally 2000 queries.
If the users recommend based on content similarity, there are 381 tracks received
by users before they send queries. (373/2000 = 18.65%)
1 則留言:
Hi. glad to see you.
I am now also working on the p2p recommendation domain. Your posing actually gives me much help.
And i'm also very interesting in your experiment data. Could kindly of you offer me one copy of your data?
contact me lemonutzf@gmail.com
thx
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