Physical Sciences and Mathematics Commons^™

Fairness In Information Access Systems, Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Diaz

Computer Science Faculty Publications and Presentations

Recommendation, information retrieval, and other information access systems pose unique challenges for investigating and applying the fairness and non-discrimination concepts that have been developed for studying other machine learning systems. While fair information access shares many commonalities with fair classification, there are important differences: the multistakeholder nature of information access applications, the rank-based problem setting, the centrality of personalization in many cases, and the role of user response all complicate the problem of identifying precisely what types and operationalizations of fairness may be relevant.

In this monograph, we present a taxonomy of the various dimensions of fair information access and …

5Th Kidrec Workshop: Search And Recommendation Technology Through The Lens Of A Teacher, Monica Landoni, Theo Huibers, Maria Soledad Pera, Jerry Alan Fails

Computer Science Faculty Publications and Presentations

In this past year, the role of technology to support education has been more prominent than ever. This has prompted us to focus the 5^th Edition of the International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec) around a major stakeholder when it comes to technology adoption for the classroom: the teacher. Much like in the previous editions of the workshop, our priority remains understanding what is good when it comes to information retrieval systems for children, this time from the perspectives of teachers. In order to control scope of our discussion and …

Estimation Of Fair Ranking Metrics With Incomplete Judgments, Ömer Kırnap, Fernando Diaz, Asia Biega, Michael Ekstrand, Ben Carterette, Emine Yilmaz

Computer Science Faculty Publications and Presentations

There is increasing attention to evaluating the fairness of search system ranking decisions. These metrics often consider the membership of items to particular groups, often identified using protected attributes such as gender or ethnicity. To date, these metrics typically assume the availability and completeness of protected attribute labels of items. However, the protected attributes of individuals are rarely present, limiting the application of fair ranking metrics in large scale systems. In order to address this problem, we propose a sampling strategy and estimation technique for four fair ranking metrics. We formulate a robust and unbiased estimator which can operate even …

3Rd Kidrec Workshop: What Does Good Look Like?, Theo Huibers, Jerry Alan Fails, Natalia Kucirkova, Monica Landoni, Emiliana Murgia, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Today’s children spend considerable time online, searching and receiving information from various websites and apps. While searching for information, e.g. for school or hobbies, children use search systems to locate resources and receive site recommendations that might be useful for them. The call for good, reliable, child-friendly systems has been made many times and the thesis that the algorithms of “adult” information systems are not necessarily suitable or fair for children is widely accepted. However, there is still no clear and balanced view on what makes one search/recommendation system for children good or better than other systems, nor on what …

A Novel Root Based Arabic Stemmer, Mohammed N. Al-Kabi, Saif A. Kazakzeh, Belal M. Abu Ata, Saif A. Al-Rababah, Izzat M. Alsmadi

Computer Science Faculty Publications and Presentations

Stemming algorithms are used in information retrieval systems, indexers, text mining, text classifiers etc., to extract stems or roots of different words, so that words derived from the same stem or root are grouped together. Many stemming algorithms were built in different natural languages. Khoja stemmer is one of the known and widely used Arabic stemmers. In this paper, we introduced a new light and heavy Arabic stemmer. This new stemmer is presented in this study and compared with two well-known Arabic stemmers. Results showed that accuracy of our stemmer is slightly better than the accuracy yielded by each one …