Requirements for Processing Datasets for Recommender Systems

Preliminary Experiences from Three Case Studies

Giannis StoitsisUniversity of Alcala, Spain

Agro-Know Technologies, Greece

RecSys Challenge 2012, Dublin

the learning case

• technology-enhanced learning investigates how information and communication technologies can be used to support learning and teaching, and competence development throughout life.

• various levels/contexts– school– higher education and research– vocational education and training– adult education

recommend resources in moodle

recommend resources in learning portal

handling multiple, diverse sets & streams

• various types of social data• different schemas and formats• multiple languages and dimensions

Single criteria Multi-criteria

why?

• support various usage and recommendation scenarios

• combining data from various sources may boost the way recommender work in education– bigger data– federated recommender systems– open science platform

a European social data infrastructure for learning

Aggregation of metadata, social and usage data

Social Data

Anonymised

Federated Recommendation

services

Social Data

Social Data

Social Data

…portals…

Metadata per URI

Metadata

Metadata

Metadata

Resolution services

API API API API

Social Data

challenges

• define common metadata schema• harvest/crawl social data• transform each social data schema• uri resolution• scalability• anonymised approach• develop item-based non personalized

algorithms that can perform well

our open science case study

web app for testing neighborhood-based recommendation algorithms with multi-criteria rating dataset

Login

Import dataset (sql,

csv, xml) Create datasetPrepare

dataset

Transfom dataset

I need more!!!

Data characteristics

Visualize dataset Visualize

resultsExport results

RecSys researcher/ developer

Export data (sql, csv)

Refine data

Cloud/Grid infra

Social Data

Monte Carlo Simulator

architecture

Recommenderservices

Social Data

Social Data

API

Components

API

Refine and transformImport Visualize Prepare/

processEvaluate

Web UI Developers

experience from Mendeley case

experience from multi-criteria rating dataset from a teachers portal

e.g. integration in classroom, relevance to topics, ability to help

students learn

Correlation Weight Threshold valueSize of the neighborhood

DEMO