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Bias and social aspects in search and recommendation : first International Workshop, BIAS 2020, Lisbon, Portugal, April 14, Proceedings / Ludovico Boratto, Stefano Faralli, Mirko Marras, Giovanni Stilo (eds.).
- Format:
- Book
- Conference/Event
- Author/Creator:
- BIAS (WORKSHOP) (1ST : 2020 : ONLINE)
- Conference Name:
- International Workshop on Algorithmic Bias in Search and Recommendation (1st : 2020 : Online)
- Series:
- Communications in computer and information science ; 1245.
- Communications in Computer and Information Science ; 1245
- Language:
- English
- Subjects (All):
- Discrimination.
- Recommender systems (Information filtering).
- Recommender systems (Information filtering)--Congresses.
- Information retrieval--Congresses.
- Information retrieval.
- Discrimination--Congresses.
- Genre:
- Conference papers and proceedings.
- Physical Description:
- 1 online resource (216 pages).
- Other Title:
- BIAS 2020
- Place of Publication:
- Cham : Springer, 2020.
- System Details:
- text file
- Contents:
- 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.
- Notes:
- International conference proceedings.
- "Due to the COVID-19 pandemic BIAS 2020 was held virtually."
- Description based upon print version of record.
- Includes author index.
- Electronic reproduction. Ann Arbor, MI Available via World Wide Web.
- Other Format:
- Print version: Boratto, Ludovico Bias and Social Aspects in Search and Recommendation : First International Workshop, BIAS 2020, Lisbon, Portugal, April 14, Proceedings
- ISBN:
- 9783030524852
- 303052485X
- Publisher Number:
- 99985319218
- 10.1007/978-3-030-52
- Access Restriction:
- Restricted for use by site license.
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