recommendation-engine

Python recommendation engine

Is there a recommendation engine for python similar to Java Taste? ...

Tag/Keyword based recommendation

Hello I am wondering what algorithm would be clever to use for a tag driven e-commerce enviroment: Each item has several tags. IE: Item name: "Metallica - Black Album CD", Tags: "metallica", "black-album", "rock", "music" Each user has several tags and friends(other users) bound to them. IE: Username: "testguy", Interests: "python", ...

Google App Engine Database Index

I need to store a undirected graph in a Google App Engine database. For optimization purposes, I am thinking to use database indexes. Using Google App Engine, is there any way to define the columns of a database table to create its index? I will need some optimization, since my app uses this stored undirected graph on a content-based fi...

SOLR and Natural Language Parsing - Can I use it?

hey guys, my requirements are pretty similar to this: Requirements http://stackoverflow.com/questions/90580/word-frequency-algorithm-for-natural-language-processing Using Solr While the answer for that question is excellent, I was wondering if I could make use of all the time I spent getting to know SOLR for my NLP. I thought of SOL...

Media recommendation engine - Single user system - How to start

Hi guys, I want to implement a media recommendation engine. I saw a similar posts on this, but I think my requirements are bit different from those, so posting here. Here is the deal. I want to implement a recommendation engine for media players like VLC, which would be an engine that has to care for only single user. Like, it would ...

Mahout Recommendations on Binary data

Hi, I'm a newbie to mahout.My aim is to produce recommendations on binary user purchased data.So i applied item-item similarity model in computing top N recommendations for movie lens data assuming 1-3 ratings as a 0 and 4-5 ratings as a 1.Then i tried evaluating my recommendations with the ratings in the test-data but hardly there have...

Apache Mahout Advices?

Have you implemented Apache Mahout recommendation engine? any advices you can share? any other sites you know that use Mahout? thanks! ...

Movies recommendation engine conceptual database design

I am working at an movie recommendations engine and i'm facing a DB design issue. My actual database looks like this: MOVIES [ID,TITLE] KEYWORDS_TABLE [ID,KEY_ID] where ID is Foreign Key for MOVIES.id and KEY_ID is a key for a text keywords table This is not the entire DB, but i showed here what's important for my problem. I have...

pre-training a neural-network

Hi. I've set up an ANN with back-propagation as a book recommendation system. I only have one hidden layer in the network, and both the input and the output layers are books, since you should be able to enter a book and receive more book recommendations. I already have a lot of data about users and their ratings (1 to 5) for books. I...

Efficient item similarity search using sphinx

Is it possible to perform document similarity search efficiently using sphinx search? My index consists of 500k documents, each which is tagged by 5-30 different short, all lowercase stemmed words which is the data to search through. For simplicity, all tags in the database has equal weights and I'm not using phrase searching. My first a...

recommendation system data collection methodology

i am building a recommendation system in my application and i am probably going to use apache mahout, i ve to collect a big dataset, it ll be collected over a period of time...so which one is least expensive between collecting it in some sort of log file vs collecting in a DB and exporting it when i need it ...

Datasets for Apache Mahout

I am looking for datasets that can be used for implementing recommendation system usecase of Apache Mahout. I know of only MovieLens Data Sets from GroupLens Research group. Anyone knows any other datasets that can be used for recommendation system implementation? I am particularly interested in item-based data sets though other datase...

What are some ways for a reccomendation engine to deal with one time, novel and potentially important content?

Say you built a recommendation engine that would recommend you live TV shows for you to watch. For regular shows, you could do a pretty good job using collaborative filtering and the like. But say it was something like the 1969 moon landing. It's obviously an important event, you want your recommendation engine to handle that case. But y...

How to continually filter interesting data to the user?

Take an example of a question/answer site with a 'browse' slideshow that will show one question/answer page at a time. The user clicks the 'next' button and a new question/answer is presented to him. I need to decide which pages should be returned each time the user clicks 'next'. Some things I don't want and reasons why: Showing ...

Alternatives (or ways to speed up) Acts_As_Recommendable plugin for Ruby on Rails

Hi all- I am currently using the Acts_as_recommendable plugin available here. It is using the pearson correlation coefficient to find recommendations, which is pretty much exactly what I want. The problem however is scale. With more than 2000 or so items, the plugin slows considerably (with 5000 items, I see load times of about a min...

Writing a basic recommendation engine

I'm looking to write a basic recommendation engine that will take and store a list of numeric IDs (which relate to books), compare those to other users with a high volume of identical IDs and recommend additional books based on those finds. After a bit of Googling, I've found this article, which discusses an implementation of a Slope On...