Algorithmic Bias in Search and Recommendation: First International Workshop, Bias 2020, Lisbon, Portugal, April 14, Proceedings

Facets of Fairness in Search and Recommendation.- Mitigating Gender Bias in Machine Learning Data Sets.- Why Do We Need To Be Bots? What Prevents Society From Detecting Biases in Recommendation Systems.- Effect of Debiasing on Information Retrieval.- Matchmaking Under Fairness Constraints: a Speed Dating Case Study.- Recommendation Filtering ? la Carte for Intelligent Tutoring Systems.- Bias Goggles - Exploring the bias of Web Domains through the Eyes of the Users.- Data Pipelines for Personalized Exploration of Rated Datasets.- Beyond Accuracy in Link Prediction.- A Novel Similarity Measure for Group Recommender Systems with Optimal Time Complexity.- What Kind of Content are you Prone to Tweet? Multi-topic Preference Model for Tweeters.- Venue Suggestion Using Social-Centric Scores.- The Impact of Foursquare Checkins on Users' Emotions on Twitter.- Improving News Personalization through Search Logs.- Analyzing the Interaction of Users with News Articles to Create Personalization Services.- Using String-Comparison measures to Improve and Evaluate Collaborative Filtering Recommender Systems.- Enriching Product Catalogs with User Opinions.

• Format: Paperback
• Language: English
• ISBN: 3030524841
• ISBN13: 9783030524845
• Release Date: July 2020
• Publisher: Springer
• Length: 205 Pages
• Weight: 0.69 lbs.
• Dimensions: 0.5" x 6.1" x 9.2"