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Filters
The Stereotyping Problem in Collaboratively Filtered Recommender Systems
[article]
2021
arXiv
pre-print
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Recommender systems play a crucial role in mediating our access to online information. ...
We show that such algorithms induce a particular kind of stereotyping: if preferences for a set of items are anti-correlated in the general user population, then those items may not be recommended together ...
Collaborative filtering and matrix factorization. Collaborative filtering (CF) is one of the most widely used methods for building large-scale recommender systems [15, 30] . ...
arXiv:2106.12622v2
fatcat:7l7rqxqjwffkpgdftgph5hkl2m
A multi-agent brokerage platform for media content recommendation
2015
International Journal of Applied Mathematics and Computer Science
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The recommendation service is a rule-based switch hybrid filter, including six collaborative and two content-based filters. ...
The proposed system provides, to our knowledge, an excellent holistic solution to the problem of recommending multimedia contents. ...
Acknowledgment This work was partially supported by the ERDF-European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by national funds through FCT-Fundação ...
doi:10.1515/amcs-2015-0038
fatcat:wbcxrlu6bvc2len6wk4dt2ctle
Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems
[chapter]
2002
Lecture Notes in Computer Science
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Collaborative filtering is an often successful method for personalized item selection in Recommender systems. ...
Characterized by the system's inability to select recently added items, the latency problem appears because new items in a collaborative filtering system must be reviewed before they can be recommended ...
Traditional Recommender systems also encounter the latency problem [9] , i.e. new items incorporated into a Recommender system cannot be used in collaborative recommendations before a substantial amount ...
doi:10.1007/3-540-46119-1_29
fatcat:cobdy3nsbzgsbdpaa5pdcjxvba
WS4_Paper1_Veloso_Malheiro_Burguillo_Foss
2017
Figshare
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Typically, recommendation algorithms are unable to make recommendations for new users due to the inherent lack of information, i.e., the cold start problem. ...
When compared with the standard average user stereotype, the results with the demographic stereotypes show a significant improvement in terms of classification accuracy, ...
ACKNOWLEDGMENTS This work was partially financed by the European Regional Development Fund (ERDF) through the Operational Programme for Competitiveness and Internationalisation (COM-PETE Programme), within ...
doi:10.6084/m9.figshare.5067265.v1
fatcat:3uudxo3hnzgvnk2qj6h5t2wfpi
Application Domain and Functional Classification of Recommender Systems—A Survey
ENGLISH
2008
DESIDOC Journal of Library & Information Technology
ENGLISH
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To address the problem of information overload and to sift all available information sources for useful information, recommender systems or filtering systems have emerged. ...
Filtering information or generation of recommendations by the recommender systems mimic the process of information retrieval systems by incorporating advanced profile building techniques, item/user representation ...
Collaborative Filtering Systems The term collaborative filtering was coined by Doug Terry at Xerox PARC in the early nineties. ...
doi:10.14429/djlit.28.3.174
fatcat:yw6e6dms7jcdrl5i6kskma3amy
Toward User Profile Representation in Adapted Mediation Systems
2016
Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
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for providing personalized information access in order to make a comparison and identify the most appropriate for our context in mediation systems. ...
For the same purpose, mediation systems have to identify user preferences in order to offer him the most relevant information .In this work we discuss different representations of user profile models designed ...
The principal disadvantage of Collaborative filtering systems is the Cold-Start problem which cannot produce recommendations if there are no ratings available. ...
doi:10.5220/0006043000810087
dblp:conf/ic3k/OuaftouhZI16
fatcat:3tejfdn3ljdibftyzqsyu2numu
Establishing User Profiles in the MediaScout Recommender System
2007
2007 IEEE Symposium on Computational Intelligence and Data Mining
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The MediaScout recommender engine uses a novel stereotype-based recommendation engine. Upon the registration of new users the system must decide how to classify the new users to existing stereotypes. ...
In this paper we present a method to achieve this classification through an anytime, interactive questionnaire, created automatically upon the generation of new stereotypes. ...
Collaborative Filtering Collaborative filtering stems from the idea that people looking for recommendations often ask for the advise of friends. ...
doi:10.1109/cidm.2007.368912
dblp:conf/cidm/ShaniRMNPB07
fatcat:tgl77oapufhwppwreufxjbupue
:{unav)
2012
Artificial Intelligence Review
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The idea of personalized search engines, intelligent software agents, and recommender systems has been widely accepted among users who require assistance in searching, sorting, classifying, filtering and ...
In this paper, we present a state-of-the-art taxonomy of intelligent recommender agents on the Internet. ...
Acknowledgements Miquel Montaner wishes to express sincere appreciation to the people at Intelligent Software Agents Group in the Robotics Institute of the Carnegie Mellon University, where the major part ...
doi:10.1023/a:1022850703159
fatcat:ixurzjumvvaazkie5qshol6yii
Hybrid Adaptation of Web-Based Systems User Interfaces
[chapter]
2004
Lecture Notes in Computer Science
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We can distinguish demographic, content-based, and collaborative recommendations. The combination of these approaches that is called hybrid adaptation enables to overcome their disadvantages. ...
The interface adaptation is one of the methods for increasing the web-based system usability, especially when we consider differences among the population of users. ...
Finally, the collaborative filtering uses the feedback from a set of some how similar people concerning a set of items in order to make recommendations. ...
doi:10.1007/978-3-540-24688-6_66
fatcat:hurhzqpuffea3liwtalmhnbr2m
Social Network for Elderly
2012
International Conference on Innovations for Community Services
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The work presented here demonstrates ad esign and implementation of asocial network system for elderly,including arecommender system, which will recommend relevant cultural and social events, and friends ...
The current projected scenario estimates that the median age of the population in the European Union will have risen to 48 years, up from 38.5 in 2005. ...
Acknowledgements Parts of this work has been carried out in context of the co-living project, which is supported by the EU commission and the Research Council of Norway through the Ambient Assisted Living ...
dblp:conf/iics/GulbrandsenFGMSSVMK12
fatcat:ep54ifvhanbsvcixnwpcxmr7j4
Survey on Recommendation System
2016
International Journal of Computer Applications
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Keywords Recommendation system, content based filtering, collaborative filtering , hybrid approach. ...
The recommendation system (RS) is crucial in many applications on the web. ...
Collaborative filtering is totally depends on similar neighbor in the system, but if these similar neighbors are not available in the system in the initial phase that is known as -cold-start‖ problem. ...
doi:10.5120/ijca2016908821
fatcat:r4vl4aqmw5edzgb7jf7okpx4ze
PNS: A Personalized News Aggregator on the Web
[chapter]
2008
Studies in Computational Intelligence
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In addition to the presentation of the basic system, we present here the results of a user study, indicating the merits of the system, as well as ways to improve it further. ...
The system collects news from HTML and RSS Web documents by using source-specific information extraction programs (wrappers) and parsers, organizes them according to pre-defined news categories and constructs ...
Their feedback is invaluable to us and we promise to do our best to improve the system in the directions that these comments point at. ...
doi:10.1007/978-3-540-77471-6_10
fatcat:j4l7j7tmzbamfi3tr2gdmwz2cq
The Melvyl Recommender Project
2006
D-Lib Magazine
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RECOMMENDER SYSTEMS: CHARACTERISTICS, STRENGTHS, AND KNOWN PROBLEMS The term collaborative filtering was first introduced in 1992 by a Xerox PARC team experimenting with email filtering systems; early ...
Recommender systems, typically in the form of either a collaborative filtering system (CF), a content-based filtering system (CBF), or a hybrid of the two (CF-CBF) offer the possibility of recommending ...
Zhang, Xiangmin Issues of applying collaborative filtering recommendations in information retrieval This free server (including source code) allows anyone to easily set up a recommendation system. ...
doi:10.1045/december2006-whitney
fatcat:nxqoitobcnetlpvcy3lul2ac7q
Collaborative Filtering Recommender Systems
2011
Foundations and Trends® in Human–Computer Interaction
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Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. ...
Research in the field is moving in the direction of a richer understanding of how recommender technology may be embedded in specific domains. ...
In describing use and evaluation of recommender systems, including collaborative filtering systems, we typically focus on two tasks. ...
doi:10.1561/1100000009
fatcat:34jiby3txreetnp2n4ew5q7swu
Personal recommender systems for learners in lifelong learning networks: the requirements, techniques and model
2008
International Journal of Learning Technology
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This article argues that there is a need for Personal Recommender Systems (PRSs) in Learning Networks (LNs) in order to provide learners advice on the suitable learning activities to follow. ...
An initial model for the design of such systems in LNs and a roadmap for their further development are presented. ...
Acknowledgement The Authors' efforts were (partly) funded by the European Commission in TENCompetence (IST-2004-02787) (http://www.tencompetence.org). ...
doi:10.1504/ijlt.2008.019376
fatcat:pphvihryvrhb5ewggairb46msm
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