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Existence Conditions for Hidden Feedback Loops in Online Recommender Systems
P. 267-274.
Anton Khritankov, Pilkevich A.
Makarov I., Gerasimova O., Sulimov P. et al., , in : Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science. Vol. 11179.: Berlin : Springer, 2018. P. 32-38.
Co-authorship networks contain invisible patterns of collaboration among researchers. The process of writing joint paper can depend of different factors, such as friendship, common interests, and policy of university. We show that, having a temporal co-authorship network, it is possible to predict future publications. We solve the problem of recommending collaborators from the point of ...
Added: September 5, 2018
Ahmed Munna M. T., Delhibabu R., , in : Intelligent Information and Database Systems: 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, April 7–10, 2021, Proceedings. : Springer, 2021. P. 782-795.
Nowadays, due to the growing demand for interdisciplinary research and innovation, different scientific communities pay substantial attention to cross-domain collaboration. However, having only information retrieval technologies in hands might be not enough to find prospective collaborators due to the large volume of stored bibliographic records in scholarly databases and unawareness about emerging cross-disciplinary trends. To ...
Added: January 14, 2021
Новиков О. В., Прикладная информатика 2013 № 5(47) С. 29-34
This article represents different techniques for building fast recommender systems based on dimension reduction and classification of web-site usage data. Description of different web-site types that use recommender systems is provided. ...
Added: October 28, 2013
Leksin V., Nikolenko S. I., , in : Proceedings of the 6th International Conference on Similarity Search and Applications (SISAP 2013), Lecture Notes in Computer Science. Vol. 8199.: Berlin, Heidelberg : Springer, 2013. P. 206-212.
An important characteristic feature of recommender systems for web pages is the abundance of textual information in and about the items being recommended (web pages). To improve recommendations and enhance user experience, we propose to use automatic tag (keyword) extraction for web pages entering the recommender system. We present a novel tag extraction algorithm that ...
Added: September 27, 2013
Саляева М. С., Vizgunov A. N., В кн. : Современные проблемы в области экономики, менеджмента, бизнес-информатики, юриспруденции социально-гуманитарных наук: материалы XI научно-практической конференции студентов и преподавателей НИУ ВШЭ - Нижний Новгород. : Н. Новгород : Нижегородский филиал НИУ ВШЭ, 2013. Гл. 1. С. 195-197.
В статье рассмотрены вопросы использования социальных сетей для обучения иностранному языку. В контексте поставленной задачи создан прототип информационной системы, который позволяет использовать алгоритмы рекомендательных систем для повышения эффективности обучения. ...
Added: February 5, 2014
Ignatov D. I., Ненова Е. Н., Konstantinov A. V. et al., , in : Artificial Intelligence: Methodology, Systems, and Applications 16th International Conference, AIMSA 2014, Varna, Bulgaria, September 11-13, 2014. Proceedings. Vol. 8722.: Dordrecht, L., Cham, Heidelberg, NY : Springer, 2014. P. 47-58.
We propose a new approach for Collaborative filtering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis. In a series of experiments on real data (MovieLens dataset) we compare the approach with an SVD-based one in terms of Mean Average Error (MAE). One of the experimental consequences is that it is enough to ...
Added: October 20, 2014
Prague : CEUR Workshop Proceedings, 2014
The first and the second edition of the FCA4AI Workshop showed that many researchers working in Artificial Intelligence are indeed interested by a well-founded method for classi- fication and mining such as Formal Concept Analysis (see http://www.fca4ai.hse.ru/). The first edition of FCA4AI was co-located with ECAI 2012 in Montpellier and published as http://ceur-ws.org/Vol-939/ while the ...
Added: September 12, 2014
Alekseyev A., Nikolenko S. I., , in : 5th Conference on Analysis of Images, Social Networks, and Text (AIST 2016). : Springer, 2017.
We introduce a novel approach to constructing user profiles for recommender systems based on full-text items such as posts in a social network and implicit ratings (in the form of likes) that users give them. The profiles measure a user’s interest in various topics mined from the full texts of the items. As a result, ...
Added: October 14, 2016
Bryanov K., Watson B., Pingree R. et al., Public Opinion Quarterly 2020 Vol. 84 No. S1 P. 216-235
What happens when news aggregators tailor their newsfeeds to include partisan news aimed at users with a known party preference? Relying on a custom-made news portal featuring real, timely articles, this study examines the influence of partisan news sources on participant headline exposure, clicks on news stories to read, and perceptions about the portal’s ability ...
Added: October 2, 2020
Berkovsky S., Taib R., Hijikata Y. et al., , in : UMAP 2018 - Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization. : ACM, 2018. P. 285-289.
User system trust is critical to the uptake of recommendations, and several factors of trust have been identified and compared. In this paper we present a cross-cultural, crowdsourced study examining user perceptions of nine factors of trust and link the observed differences to trust development processes and cultural dimensions. While some factors consistently instil trust, ...
Added: November 9, 2018
Ignatov D. I., Nikolenko S. I., Abaev T. et al., Expert Systems with Applications 2016 Vol. 55 P. 546-558
We present a new recommender system developed for the Russian interactive radio network FMhost. To the best of our knowledge, it is the first model and associated case study for recommending radio stations hosted by real DJs rather than automatically built streamed playlists. To address such problems as cold start, gray sheep, boosting of rankings, preference ...
Added: June 28, 2016
Kiselev D., Makarov I., IEEE Access 2022 Vol. 10 P. 123614-123621
Temporal graph networks are powerful tools for solving the cold-start problem in sequential recommender systems. However, graph models are susceptible to feedback loops and data distribution shifts. The paper proposes a simple yet efficient graph-based exploration method for the mitigation of the issues above. It adopts the counter-based state exploration from reinforcement learning to the ...
Added: September 5, 2022
Andreeva E., Ignatov D. I., Grachev A. et al., , in : Proceedings of Analysis of Images, Social Networks and Texts – 7th International Conference, AIST 2018, Moscow, Russia, July 5-7, 2018, Revised Selected Papers. Lecture Notes in Computer Science. Vol. 11179.: Berlin : Springer, 2018. P. 201-210.
In this paper (The first author is the 1st place winner of the Open HSE Student Research Paper Competition (NIRS) in 2017, Computer Science nomination, with the topic “Extraction of Visual Features for Recommendation of Products”, as alumni of 2017 “Data Science” master program at Computer Science Faculty, HSE, Moscow), we describe a special recommender ...
Added: January 23, 2019
Сендерович М. А., В кн. : Межвузовская научно-техническая конференция студентов, аспирантов и молодых специалистов им. Е.В. Арменского. : М. : МИЭМ НИУ ВШЭ, 2019. С. 223-224.
Данная работа посвящена актуальной теме автоматизации в машинном обучении на примере создания универсальной рекомендательной системы. В работе исследуются различные типы рекомендательных систем, акцент делается на подходы коллаборативной фильтрации. Изучаются методы автоматизации машинного обучения, на основе которых будет разработана данная рекомендательная система. ...
Added: October 31, 2020
Demochkin K., Savchenko A., , in : Analysis of Images, Social Networks and Texts. 8th International Conference, AIST 2019, Lecture Notes in Computer Science, Revised Selected Papers. Vol. 11832.: Cham : Springer, 2019. Ch. 26. P. 291-297.
In this paper we focus on the problem of multi-label image recognition for visually-aware recommender systems. We propose a two stage approach in which a deep convolutional neural network is firstly fine-tuned on a part of the training set. Secondly, an attention-based aggregation network is trained to compute the weighted average of visual features in ...
Added: December 22, 2019
Ignatov D. I., Sarwar S. M., Hasan M. et al., , in : Analysis of Images, Social Networks and Texts. 4th International Conference, AIST 2015, Yekaterinburg, Russia, April 9–11, 2015, Revised Selected Papers. Vol. 542: Series: Communications in Computer and Information Science.: Switzerland : Springer, 2015.
In this paper we show how several similarity measures can be combined for finding similarity between a pair of users for performing Collaborative Filtering in Recommender Systems. Through aggregation of several measures we find super similar and super dissimilar user pairs and assign a different similarity value for these types of pairs. We also introduce ...
Added: November 24, 2015
Ignatov D. I., Kaminskaya A. Y., Malioukov A. et al., , in : Proceedings of International Conference on Conceptual Structures 2014. Vol. 8577: Graph-Based Representation and Reasoning.: Springer, 2014. P. 287-292.
This paper considers a recommender part of the data anal- ysis system for the collaborative platform Witology. It was developed by the joint research team of the National Research University Higher School of Economics and the Witology company. This recommender sys- tem is able to recommend ideas, like-minded users and antagonists at the respective phases ...
Added: June 9, 2014
Maxim Borisyak, Zykov R., Noskov A., / Cornell University. Series arxiv :: cs :: Cornell University "arxiv :: cs :: Cornell University". 2015.
Classical approaches in recommender systems such as collaborative filtering are concentrated mainly on static user preference extraction. This approach works well as an example for music recommendations when a user behavior tends to be stable over long period of time, however the most common situation in e-commerce is different which requires reactive algorithms based on ...
Added: November 9, 2015
Ignatov D. I., Poelmans J., , in : Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems. : Hershey : IGI Global, 2012. Ch. 8. P. 185-195.
Recommender systems are becoming an inseparable part of many modern Internet web sites and web shops. The quality of recommendations made may significantly influence the browsing experience of the user and revenues made by web site owners. Developers can choose between a variety of recommender algorithms; unfortunately no general scheme exists for evaluation of their ...
Added: December 3, 2012
Ignatov D. I., Kaminskaya A. Y., Konstantinova N. et al., , in : Proceedings of The 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2014, 11-14 August 2014 Warsaw, Poland. : Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014. P. 327-335.
This paper discusses the recommender models and methods for crowdsourcing platforms. These models are based on modern methods of data analysis of object-attribute data, such as Formal Concept Analysis and biclustering. In particular, the paper is focused on the solution of two tasks – idea and antagonists recommendation – on the example of crowdsourcing platform ...
Added: June 9, 2014
Gerasimova O., Makarov I., , in : Advances in Computational Intelligence. IWANN 2019. : Berlin : Springer, 2019. P. 667-677.
In this paper, we study the problem of predicting quantity of collaborations in co-authorship network. We formulated our task in terms of link prediction problem on weighted co-authorship network, formed by authors writing papers in co-authorship represented by edges between authors in the network. Our task is formulated as regression for edge weights, for which ...
Added: July 29, 2019
Ignatov D. I., Poelmans J., Dedene G. et al., Lecture Notes in Computer Science 2012 Vol. 7143 LNCS P. 195-202
The topic of recommender systems is rapidly gaining interest in the user-behaviour modeling research domain. Over the years, various recommender algorithms based on different mathematical models have been introduced in the literature. Researchers interested in proposing a new recommender model or modifying an existing algorithm should take into account a variety of key performance indicators, ...
Added: February 6, 2013
Anna Averchenkova, Alina Akhmetzyanova, Sudarikov K. et al., , in : Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics. : Springer, 2020. P. 101-119.
Nowadays, a lot of scientists’ works aim to improve the quality of people’s life but it could be quite complicated without building a successful collaboration. Productive partnerships can increase research efficiency in many cases and make a huge impact on society. However, today there is no clear way to find such collaborators. In this paper, ...
Added: February 27, 2020