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

ISBN-13: 9783030524845 / Angielski / Miękka / 2020 / 205 str.

Ludovico Boratto; Stefano Faralli; Mirko Marras

Spis treści

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 à 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.