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Scraping publicly-accessible Letterboxd data for movie recommendations
Scraping publicly-accessible Letterboxd data and creating a movie recommendation model with it that can generate recommendations when provided with a Letterboxd username. A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). All movies in the full dataset that the user has not rated are run through the model for predicted scores and the items with the top predicted scores are returned. ...
panFMP is a generic framework suitable for harvested XML metadata that is searchable through Apache Lucene without any additional RDBMS. Fields can be defined by XPath allowing for full text queries on all types of fields including numerical ranges.
The code was moved to Github: https://github.com/pangaea-data-publisher/panfmp
Allows viewing of .cbr and .cbz comic book archives over an internet connection via a web browser. Extracts images from archives on demand, resizing them if necessary in order to be bandwidth/browser friendly.
Provides a web-based learning platform for highschool or college courses in quantitative disciplines such as physics. Numerical and various types of MC-questions with answers depending on random parameters are supported.
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The main purpose of "python2xlw" is to create an Excel-compatible file which can be sent to users via the web as an excel application. The motivation is mainly to support the display of XY Scatter plots and tabular numerical data(eg engineering data)