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Collaborator Recommender System
P. 101-119.
Anna Averchenkova, Alina Akhmetzyanova, Sudarikov K., Stanislav Petrov, Makarov I., Pendiukhov M., Zhukov L. E.
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, we propose a recommender system for the scientists from the Higher School of Economics university to help them find co-authors for their prospective studies.
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
Demochkin K. V., Savchenko A., Journal of Physics: Conference Series 2019 Vol. 1368 No. 032016 P. 1-7
In this paper we focus on the problem of user interests’ classification in visual product recommender systems. We propose the two-stage procedure. At first, the visual features are learned by fine-tuning the convolutional neural network, e.g., MobileNet. At the second stage, we use such learnable pooling techniques as neural aggregation network and context gating in ...
Added: November 29, 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
Karpov N., Shashkin P, , in : WI '17 Proceedings of the International Conference on Web Intelligence. : ACM, 2017. P. 1069-1071.
Improving user experience through personalized recommendations is crucial to organizing the abundance of data on news websites. Modeling user preferences based on implicit feedback has recently gained lots of attention, partly due to growing volume of web generated click stream data. Matrix factorization learned with stochastic gradient descent has successfully been adopted to approximate various ...
Added: November 14, 2017
Ignatov D. I., Poelmans J., Dedene G. et al., , in : Perception and Machine Intelligence. First Indo-Japan Conference, PerMIn 2012, Kolkata, India, January 12-13, 2011, Proceedings. Vol. 7143.: Berlin, Heidelberg : Springer, 2012. 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: December 3, 2012
Ignatov D. I., Ахматнуров М., , in : Proceedings of the Twelfth International Conference on Concept Lattices and Their Applications Clermont-Ferrand, France, October 13-16, 2015. Vol. 1466.: Clermont-Ferrand : CEUR Workshop Proceedings, 2015. P. 99-110.
In this work we propose and study an approach for collaborative filtering, which is based on Boolean matrix factorisation and exploits additional (context) information about users and items. To avoid similarity loss in case of Boolean representation we use an adjusted type of projection of a target user to the obtained factor space. We have ...
Added: October 23, 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
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
Ignatov D. I., Poelmans J., Zaharchuk V. V., , in : CDUD'11 – Concept Discovery in Unstructured Data Workshop co-located with the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC-2011), June 2011, Moscow, Russia. Issue 757.: M. : Higher School of Economics Publishing House, 2011. P. 122-126.
In this paper we propose two new algorithms based on biclustering analysis, which can be used at the basis of a recommender system for educational orientation of Russian School graduates. The first algorithm was designed to help students make a choice between different university faculties when some of their preferences are known. The second algorithm ...
Added: December 3, 2012
Ignatov D. I., Kuznetsov S., , in : CLA 2008. Proceedings of the Sixth International Conference on Concept Lattices and Their Applications. : Olomouc : Palacky University, 2008. P. 157-166.
The problem of detecting terms that can be interesting to the advertiser is considered. If a company has already bought some advertising terms which describe certain services, it is reasonable to find out the terms bought by competing companies. A part of them can be recommended as future advertising terms to the company. The goal ...
Added: December 9, 2012
Los Alamitos, Washington, Tokyo : IEEE Computer Society, 2014
This volume contains the papers selected for presentation at the 2014 IEEE/WIC/ACM International Conference on Web Intelligence (WI'14), held as part of the 2014 Web Intelligence Congress (WIC'14) at the University of Warsaw, Warsaw, Poland, from 11 to 14 in August, 2014. The conference was sponsored and co-organized by the IEEE Computer Society, the Web ...
Added: June 9, 2014
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
Makarov I., Kiselev D., Gerasimova O. et al., Network Science 2020 P. 1-13
In this paper, we study network feature engineering for the problem of future co-author recommendation, also called collaborator recommender system. We present a system, which uses authors' research interests and existing collaboration information to predict missing and most probable in the future links in the co-authorship network. The recommender system is stated as a link ...
Added: October 27, 2020
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
Дёмочкин К. В., Savchenko A., В кн. : Сборник трудов V Международной конференции и молодёжной школы "Информационные технологии и нанотехнологии" (ИТНТ 2019). : [б.и.], 2019.
In this paper we focus on the problem of user prediction in visual product recommender systems based on the given set of photos of products purchased by the user previously. We studied neural aggregation methods for image features extracted by the deep neural networks. We propose the novel two-stage algorithm. At first, the image features ...
Added: December 4, 2018
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
Makarov I., Gerasimova O., , in : Proceedings of the 14th International Workshop on Semantic and Social Media Adaptation and Personalization. : NY : IEEE, 2019. P. 1-6.
In this paper, we study the problem of predicting collaborations in co-authorship network. We formulated our task in terms of link prediction problem on weighted co-authorship network, in which authors play the role of nodes, and weighted edges connecting two authors are formed by storing either a number or quality metric of research papers co-authored ...
Added: July 30, 2019
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., 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
Savchenko A., Дёмочкин К. В., Savchenko L., Optical Memory and Neural Networks (Information Optics) 2020 Vol. 29 No. 4 P. 297-304
In this paper, we analyze effective methods of multi-label classification of image sets in development of visual recommender systems. We propose a two-step algorithm, which at the first step performs fine-tuning of a convolutional neural network for extraction of visual features. At the second stage, the algorithm concatenates the obtained feature vectors of each image ...
Added: October 25, 2019
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
M. : Higher School of Economics Publishing House, 2011
Concept discovery is a Knowledge Discovery in Databases (KDD) research field that uses human-centered techniques such as Formal Concept Analysis (FCA), Biclustering, Triclustering, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often ...
Added: December 3, 2012
Ignatov D. I., Корнилов Д. И., , in : Proceedings of the International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at IJCAI 2015). : Buenos Aires : [б.и.], 2015. P. 87-98.
We propose a new algorithm for recommender systems with numeric ratings which is based on Pattern Structures (RAPS). As the input the algorithm takes rating matrix, e.g., such that it contains movies rated by users. For a target user, the algorithm returns a rated list of items (movies) based on its previous ratings and ratings ...
Added: October 23, 2015
Makarov I., Gerasimova O., Sulimov P. et al., , in : Proceedings of WebSci’18 Main Conference Poster Session. : Aachen : CEUR Workshop Proceedings, 2018. Ch. 1. P. 1-2.
In this paper we show that for a given co-authorship network we could construct a recommender system for searching collaborators with similar research interests defined via keywords and topic modelling. We suggest new link embedding method and evaluate our model on National Research University Higher School of Economics (NRU HSE) co-authorship network. ...
Added: September 5, 2018