AnimeRecs is a project that aims to provide accurate and useful anime recommendations. It contains several components. All components ultimately serve the needs of AnimeRecs.Web, an ASP.NET MVC web application for giving anime recommendations based on the user's myanimelist.net account.

All components are licensed under the GPL version 3. See LICENSE.txt for license information.

AnimeRecs.RecEngine: Core interfaces and classes forming a generic top-N recommendation framework and some basic generic recommendation algorithms. Flexibility is favored over efficiency or simplicity. Algorithms here make as few assumptions about their training data and input as possible. For example, it is possible to make recommendation algorithms that use a different form of input from the usual (user, item, rating) triples, produce more detailed output than a simple list of recommendations, or that avoid making recommendations based on certain criteria (for example, do not recommend an anime that is a sequel if the user has not seen the first anime yet). Also included is code for evaluating the effectiveness of recommendation algorithms. Rec sources defined here are domain-agnostic.

AnimeRecs.RecEngine.MyMediaLite: Integration of the MyMediaLite recommendation framework with the AnimeRecs.RecEngine framework, allowing you to use any class inheriting from MyMediaLite.RatingPrediction.RatingPredictor and implementing MyMediaLite.RatingPrediction.IFoldInRatingPredictor with the AnimeRecs.RecEngine framework.

AnimeRecs.RecEngine.MAL: myanimelist.net-specific recommendation algorithms. These algorithms usually proxy to ones in AnimeRecs.RecEngine and perhaps do some filtering. For example, specials are never recommended because the user may not have seen the anime the special relates to and a user probably does not need a recomendation to tell them to watch the specials of anime they like. If specials are not filtered out, they tend to take up a decent amount of space in a recommendation list. Other filtering includes deciding when to tell algorithms to use the score of an in-progress anime and allowing dropped anime to not count towards an anime's popularity.

AnimeRecs.DAL: SQL scripts for initializing a PostgreSQL database of myanimelist.net users, anime, and ratings, and data access code for it.

AnimeRecs.FreshenMalDatabase: Program that gets N users that are not in the PostgreSQL database and inserts their anime list. The number of users in the database is capped. If the cap is 5000 users, there are 5000 users in the database, and you tell the program to get 100 new users, it will put 100 new users in the database and delete the 100 users that have been in the database the longest. This allows you to maintain a database with a fixed number of users that does not get stale.

AnimeRecs.UpdateStreams: Tool for maintaining the streaming_service_anime_map table.

AnimeRecs.MalEvaluationRunner: Program for evaluating MAL recommendation sources.

AnimeRecs.RecService: Service that listens on a socket and responds to requests for anime recommendations and commands to load/unload recommendation sources.

AnimeRecs.RecService.DTO: Definitions of objects passed between rec service clients and the rec service.

AnimeRecs.RecService.ClientLib: Client library for interacting with AnimeRecs.RecService.

AnimeRecs.RecService.Client: Command-line rec service client application for controlling a running rec service and testing recommendation sources.

AnimeRecs.Web: Nancy web application that gives recommendations based on a user's myanimelist.net account

Note that myanimelist.net now blocks programmatic HTTP requests unless your application is whitelisted so you will not be able to populate a user database or test normally. What you can do is get a database from somewhere and enable the config option for getting users' anime list from the database instead of from myanimelist.net.

To set up a development environment you will need to install the following:

• Visual Studio 2013 Community Edition
• PostgreSQL (http://www.postgresql.org/) (9.1.x supported, earlier versions will probably work also)

Set up instructions for Linux assume Ubuntu or Debian. If you want to use a different distro, good luck, you're on your own. I have found Ubuntu and Debian to have good Mono support.

To build for Mono on Linux, you must use xbuild (or MonoDevelop set to use xbuild) on Linux. Cross-compiling is not supported. Building for .NET vs. Mono have slight differences. The only difference in run-time behavior is that when running on Windows recservice is existing by pressing any key, while on Linux it is terminated by sending a SIGINT (ctrl+c) or SIGTERM.

Building on Linux with xbuild: $ xbuild /t:build /p:Configuration=Debug /p:Platform=AnyCPU xyz.csproj

1. Set your locale to UTF-8. This ensures that Postgres that does not install with a default of ASCII and prevent you from creating a database that uses UTF-8 as its encoding. $ sudo update-locale LANG=en_US.UTF-8

2. Increase the maximum shared memory size from the ridiculously small default. This step is optional but will allow you to later increase the amount of shared memory Postgres can use. edit /etc/sysctl.conf, add line kernel.shmmax=134217728 (for 128 MB)

$ sudo service procps start

3. Install the postgres package

4. Set a password for the "postgres" PostgreSQL user and allow Linux users other than postgres to log in as the "postgres" PostgreSQL user. Using the postgres user is not necessarily ideal in a production environment, but it's easiest to set up for development.

$ su - postgres $ psql -d template1 -c "ALTER USER postgres WITH PASSWORD 'testpw';" $ exit

1. Install pgdbsc. On Windows, download the installer for the latest version from the releases page. On Linux, follow the instructions on the readme to add the dbsc package repository and install the package.
2. Open a command prompt to AnimeRecs.DAL\DB Init Scripts. On Windows, run pgdbsc checkout -u postgres -p testpw -dbCreateTemplate windows_create_template.sql. On Linux, run pgdbsc checkout -u postgres -p testpw -dbCreateTemplate linux_create_template.sql

Note that this cannot be done in a development environment because MAL will reject requests that do not have an API key. If you are interested in developing for animerecs, contact me and I can provide you with a usable database.

1. Edit App.Debug.config (App.DebugMono.config on Linux) in AnimeRecs.FreshenMalDatabase. Edit the connection string to use your Postgres username and password. Set UsersPerRun to 1000 (or however many users you want to have in the database initially).
2. Compile and run AnimeRecs.FreshenMalDatabase. This will populate the database with users from myanimelist.net's "recently online users" page. This will take some time to run.

Connect to the animerecs database and run AnimeRecs.DAL/DB Init Scripts/StreamMappings.sql. On Windows you can use pgAdmin and paste the SQL in. On Linux, psql -U postgres -d animerecs -f StreamMappings.sql

Connect to the animerecs database and run AnimeRecs.DAL/DB Init Scripts/Prereqs.sql. On Windows you can use pgAdmin and paste the SQL in. On Linux, psql -U postgres -d animerecs -f Prereqs.sql

1. Edit App.Debug.config (App.DebugMono.config on Linux) in the AnimeRecs.RecService project. Edit the connection string to use your Postgres username and password. Compile AnimeRecs.RecService and run it in a command prompt.
2. Compile AnimeRecs.RecService.Client and load some rec sources, preferably at least one with the name "default". See the recclient tutorial below for how to use AnimeRecs.RecService.Client.
3. Compile and run the web site locally. Try it out. The site runs on port 8888 by default. You can just this by editing Hosting.Port in the config. You can use http://localhost:8888/?algorithm=some_rec_source to use a non-default rec source.

[Get command-line usage info] recclient.exe -h

[Load a rec source that uses average score to recommend anime] recclient.exe -c LoadRecSource -type AverageScore -name avg

[Load a rec source that requires 40 users to have rated an anime before recommending it instead of the default of 50] recclient.exe -c LoadRecSource -type AverageScore -name avg --min_users_to_count_anime=40

[Oops! That last command failed because there's already a rec source named "avg". Use the -f switch to overwrite an already-loaded rec source] recclient.exe -c LoadRecSource -type AverageScore -name avg -f --min_users_to_count_anime=40

[Get anime recommendations for the myanimelist.net user "LordHighCaptain" using the loaded rec source called "avg"] recclient.exe -c GetMalRecs -name avg -u LordHighCaptain

[Load a rec source that uses MyMediaLite's BiasedMatrixFactorization algorithm. Since we don't specify -name, it uses the name "default".] recclient.exe -c LoadRecSource -type BiasedMatrixFactorization

[Get anime recommendations using the loaded rec source called "default"] recclient.exe -c GetMalRecs -u LordHighCaptain

[Let's try reloading it with some non-default options. Use recclient.exe -h to see all possible tunable parameters] recclient.exe -c LoadRecSource -type BiasedMatrixFactorization -f -bold_driver --bias_learn_rate=0.5 recclient.exe -c GetMalRecs -u LordHighCaptain

[You decided you don't want to use the average score rec source. You can unload a rec source and make its memory available for garbage collection] recclient.exe -c UnloadRecSource -name avg

[If you have run FreshenMalDatabase to update the database you can retrain all loaded rec sources with current data] recclient.exe -c ReloadTrainingData