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Journal articles on the topic 'User profile'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

CASTELLANO, GIOVANNA, CIRO CASTIELLO, DANILO DELL'AGNELLO, ANNA MARIA FANELLI, CORRADO MENCAR, and MARIA ALESSANDRA TORSELLO. "LEARNING FUZZY USER PROFILES FOR RESOURCE RECOMMENDATION." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 18, no. 04 (2010): 389–410. http://dx.doi.org/10.1142/s0218488510006611.

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Recommender systems are systems capable of assisting users by quickly providing them with relevant resources according to their interests or preferences. The efficacy of a recommender system is strictly connected with the possibility of creating meaningful user profiles, including information about user preferences, interests, goals, usage data and interactive behavior. In particular, analysis of user preferences is important to predict user behaviors and make appropriate recommendations. In this paper, we present a fuzzy framework to represent, learn and update user profiles. The representati

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K.R.Ananthapadmanaban, Author, and S. K. Srivatsa. "Personalisation of User Profile: Creating User Profile Ontology for Tamilnadu Tourism." International Journal of Computer Applications 23, no. 8 (2011): 42–47. http://dx.doi.org/10.5120/2903-3808.

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Grida, Mohamed, Lamiaa Fayed, and Mohamed Hassan. "User Profile: Theoretical Background." International Journal of Engineering Trends and Technology 68, no. 8 (2020): 10–17. http://dx.doi.org/10.14445/22315381/ijett-v68i8p203s.

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Petersen, Francoise, Giovanni Bartolomeo, and Mike Pluke. "Personalization and User Profile Management." International Journal of Interactive Mobile Technologies (iJIM) 2, no. 4 (2008): 25. http://dx.doi.org/10.3991/ijim.v2i4.666.

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Personalization and effective user profile management will be critical to meet the individual usersâ?? needs and for achieving e-Inclusion and e-Accessibility. This paper outlines means to achieve the goal of the new ICT era where services and devices can be personalized by the users in order to meet their needs and preferences, in various situations. Behind every instance of personalization is a profile that stores the user preferences, context of use and other information that can be used to deliver a user experience tailored to their individual needs and preferences. Next Generation Network

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Ambika, Mani, and K. Latha. "Intelligence Based User Profile Generation." Applied Mechanics and Materials 573 (June 2014): 618–23. http://dx.doi.org/10.4028/www.scientific.net/amm.573.618.

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Web intelligence provides a platform that empowers internet users to determine the most appropriate and best information for their interests. It provides the ability to sense and adapt to the needs and preference of the user. The recent advancements have made it conceivable to capture the users experience and interactions with web. Consequently predicting users behaviors will expedite and enhance browsing experience. This paper proposes an intelligent approach for making the web more powerful by predicting the conduct of individual users. The main goal is to implicitly construct user profiles

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Eyharabide, Victoria, and Analía Amandi. "Ontology-based user profile learning." Applied Intelligence 36, no. 4 (2011): 857–69. http://dx.doi.org/10.1007/s10489-011-0301-4.

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Zeng, Wenjing, Rui Tang, Haizhou Wang, Xingshu Chen, and Wenxian Wang. "User Identification Based on Integrating Multiple User Information across Online Social Networks." Security and Communication Networks 2021 (May 25, 2021): 1–14. http://dx.doi.org/10.1155/2021/5533417.

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User identification can help us build more comprehensive user information. It has been attracting much attention from academia. Most of the existing works are profile-based user identification and relationship-based user identification. Due to user privacy settings and social network restrictions on user data crawl, user data may be missing or incomplete in real social networks. User data include profiles, user-generated contents (UGCs), and relationships. The features extracted in previous research may be sparse. In order to reduce the impact of the above problems on user identification, we p

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Proença, Mailson de Queiroz, Vivian Genaro Motti, Kamila Rios da Hora Rodrigues, and Vânia Paula de Almeida Neris. "Coping with Diversity - A System for End-users to Customize Web User Interfaces." Proceedings of the ACM on Human-Computer Interaction 5, EICS (2021): 1–27. http://dx.doi.org/10.1145/3457151.

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To address diverse interaction needs of heterogeneous users' groups, user interfaces must be flexible to accommodate for customization that are specific to each user profile. Although, existing web interfaces provide some flexibility, some problems still remain: a) manual adjustments carried out by end users are required for each web application; b) the flexibility provided by current web interfaces is insufficient to address diverse interaction needs of various users' profiles and c) few users are aware about such options to customize the presentation of web interfaces. To contribute to the c

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Iggui, Taous, Hassina Nacer, Youcef Sklab, and Taklit Ait Radi. "Web Application for User Profiling." International Journal of Information Systems in the Service Sector 8, no. 2 (2016): 44–56. http://dx.doi.org/10.4018/ijisss.2016040104.

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User's profiles play an important role when information systems try to meet their needs. This work presents a novel approach to build user profiles. It is based on information extraction techniques and proceeds by iterative steps. The use of different statistic metrics, Natural Language Processing (NLP) techniques and semantic descriptions (ontologies) in the authors' approach, has provided it with a good precision degree when extracting information from texts. This has been demonstrated by an application prototype which is an automatic user profile constructor, using the texts of emails job a

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Schöggl-Ernst, Elisabeth. "The Change of User Profile in the Styrian Provincial Archives." Atlanti 26, no. 2 (2016): 13–22. http://dx.doi.org/10.33700/2670-451x.26.2.13-22(2016).

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Various external and internal factors influence the user profile of an archive. The acquisitions policy of an archive is a basis for the formation of particular user groups. Shifting research themes in history and related disciplines can also be included as a reason for user profiles changing in an archive. This article examines the user profiles of the Styrian Provincial Archive over the last two decades and discusses the various causes of change.

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Замятин, Н. В., and Г. В. Смирнов. "Smart Home User Profiles." Успехи кибернетики / Russian Journal of Cybernetics 5, no. 2(18) (2024): 53–63. http://dx.doi.org/10.51790/2712-9942-2024-5-2-06.

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сформулированы проблемы умного дома, решение которых заключается в том числе в эффективном профилировании. Кратко рассмотрены платформы для умного дома пользователей. Определены профили классов пользователей с учетом их предпочтений и конфликтов предпочтений пользователей, способы их разрешения. Представлен менеджер профилей с примером программы на XML. Приведен нейросетевой алгоритм определения активности пользователей. Показана методика реализации профилей пользователей умного дома. this study presents some issues of smart home technology and proposes a solution based on user profiles. The p

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Zhou, Dong, Séamus Lawless, Xuan Wu, Wenyu Zhao, and Jianxun Liu. "A study of user profile representation for personalized cross-language information retrieval." Aslib Journal of Information Management 68, no. 4 (2016): 448–77. http://dx.doi.org/10.1108/ajim-06-2015-0091.

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Purpose – With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach – The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as va

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Nikolakopoulos, Ioannis, Charalampos Patrikakis, Antonio Cimmino, Martin Bauer, and Henning Olesen. "On the Personalization of Personal Networks - Service Provision Based on User Profiles." JUCS - Journal of Universal Computer Science 15, no. (12) (2009): 2353–72. https://doi.org/10.3217/jucs-015-12-2353.

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In this paper, we present a user profile definition scheme featuring context awareness. Though the scheme has been designed to meet the needs of web applications deployed over heterogeneous devices, emphasis is given in the deployment of the profile scheme over Personal Networks (PNs), as the personalization of the deployed applications and services in PN environments is of great importance. The proposed scheme is presented as part of an integrated framework for user profile management that takes into account (and is therefore compliant to) the existing standardization attempts. The overall ar

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Sadesh, S., and R. C. Suganthe. "Effective Filtering of Query Results on Updated User Behavioral Profiles in Web Mining." Scientific World Journal 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/829126.

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Web with tremendous volume of information retrieves result for user related queries. With the rapid growth of web page recommendation, results retrieved based on data mining techniques did not offer higher performance filtering rate because relationships between user profile and queries were not analyzed in an extensive manner. At the same time, existing user profile based prediction in web data mining is not exhaustive in producing personalized result rate. To improve the query result rate on dynamics of user behavior over time, Hamilton Filtered Regime Switching User Query Probability (HFRS-

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Okfalisa, Okfalisa, Dwi Utari Iswavigra, Hidayati Rusnedy, and Toto Saktioto. "Pemilihan Smartphone Berdasarkan Rekomendasi Profile User: Integrasi Fuzzy Analytical Hierarchy Process dan Rule Based." JURNAL SISTEM INFORMASI BISNIS 10, no. 2 (2020): 211–19. http://dx.doi.org/10.21456/vol10iss2pp211-219.

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The usability and usefulness of smartphones have been found to lack optimality. Moreover, the action of the customer appears to behave as a consumptive user instead of buying following the basic needs. In selecting the right smartphone, this study provides an alternative option for buyers. The Fuzzy Analytical Hierarchy Process (F-AHP) approach is applied by distinguishing between two distinct decision-making namely, Profile User as a user recommendation-based, and Smartphone-based selection. The suggested requirements are hobbies, areas of jobs, and the use of social network applications in d

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Liu, Dong, and Quan Yuan Wu. "Cross-Platform User Profile Matching in Online Social Networks." Applied Mechanics and Materials 380-384 (August 2013): 1955–58. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1955.

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Nowadays, it is common that people have several identities in different online social networks where their identities information is stored as user profiles. Matching cross-platform user profiles becomes a spotlight in the future research. In the paper, we propose a profile matching framework. Depending on the format of each field, different string similarity measures are adopted. Meanwhile, each fields importance is considered. At last, we evaluate the effectiveness of our proposed methods by experiments.

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Izawa, Shin, Keiko Ono, and Panagiotis Adamidis. "Diversifying Furniture Recommendations: A User-Profile-Enhanced Recommender VAE Approach." Applied Sciences 15, no. 5 (2025): 2761. https://doi.org/10.3390/app15052761.

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We propose a novel recommendation model for diversifying furniture recommendations and aligning them more closely with user preferences. Our model builds upon the Recommender Variational Autoencoder (RecVAE), known for its effectiveness and ability to overcome overfitting by linking user feedback with user representation. However, since RecVAE relies on implicit feedback data, it tends to exhibit bias towards popular items, potentially creating a recommendation filter bubble. While previous work has proposed user profiles learned from a user’s personal information and the textual data of an it

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Tamboli, Najneen, and Sathish Kumar Penchala. "User Profile Based Personalized Web Search." International Journal of Managing Public Sector Information and Communication Technologies 7, no. 3 (2016): 15–22. http://dx.doi.org/10.5121/ijmpict.2016.7302.

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Kaya, Buket. "User Profile Based Paper Recommendation System." International Journal of Intelligent Systems and Applications in Engineering 2, no. 6 (2018): 151–57. http://dx.doi.org/10.18201/ijisae.2018642079.

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Pramiyati, Titin, Iping Supriana, and Ayu Purwarianti. "Pengenalan Entitas User Profile Pada Twitter." Jurnal INKOM 8, no. 2 (2015): 103. http://dx.doi.org/10.14203/j.inkom.411.

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Atribut trust scope sebagai atribut untuk menentukan tingkat kepercayaan sumber informasi, akan diisi dengan data yang terdapat pada user profile Twitter yang dikenal sebagai Bio Twitter. Hanya saja, data tersebut harus sesuai dengan karakteristik dan fungsi dari masing-masing atribut trust scope, seperti atribut pendidikan harus diisi dengan informasi yang berkaitan dengan latar belakang pendidikan dari pemilik profil tersebut. Untuk mendapatkan data yang sesuai dengan atribut, kami melakukan named entity recognition, yang merupakan salah satu kegiatan pada proses ekstraksi informasi. Oleh ka

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PANAGIOTAKIS, SPYROS, MARIA KOUTSOPOULOU, and ATHANASSIA ALONISTIOTI. "CONTEXT-AWARENESS AND USER PROFILING IN MOBILE ENVIRONMENTS." International Journal of Semantic Computing 03, no. 03 (2009): 331–63. http://dx.doi.org/10.1142/s1793351x09000811.

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The evolution of mobile communication systems to 3G and beyond introduces requirements for flexible, customized, and ubiquitous multimedia service provision to mobile users. One must be able to know at any given time the network status, the user location, the profiles of the various entities (users, terminals, network equipment, services) involved and the policies that are employed within the system. Namely, the system must be able to cope with a large amount of context information. The present paper focuses on location and context awareness in service provisioning and proposes a flexible and

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Biswas, Pooshpanjan Roy, Alessandro Beltrami, and Joan Saez Gomez. "A testing paradigm for quantifying ICC profilers." Color and Imaging Conference 2019, no. 1 (2019): 80–85. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.15.

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To reproduce colors in one system which differs from another system in terms of the color gamut, it is necessary to use a color gamut mapping process. This color gamut mapping is a method to translate a specific color from a medium (screen, digital camera, scanner, digital file, etc) into another system having a difference in gamut volume. There are different rendering intent options defined by the International Color Consortium [5] to use the different reproduction goals of the user [19]. Any rendering intent used to reproduce colors, includes profile engine decisions to do it, i.e. looking f

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Cufoglu, Ayse, Mahi Lohi, and Colin Everiss. "Feature weighted clustering for user profiling." International Journal of Modeling, Simulation, and Scientific Computing 08, no. 04 (2017): 1750056. http://dx.doi.org/10.1142/s1793962317500568.

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Personalization is the adaptation of the services to fit the user’s interests, characteristics and needs. The key to effective personalization is user profiling. Apart from traditional collaborative and content-based approaches, a number of classification and clustering algorithms have been used to classify user related information to create user profiles. However, they are not able to achieve accurate user profiles. In this paper, we present a new clustering algorithm, namely Multi-Dimensional Clustering (MDC), to determine user profiling. The MDC is a version of the Instance-Based Learner (I

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Chen, Junpu, and Hong Xie. "An Online Learning Approach to Sequential User-Centric Selection Problems." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 6 (2022): 6231–38. http://dx.doi.org/10.1609/aaai.v36i6.20572.

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This paper proposes a new variant of multi-play MAB model, to capture important factors of the sequential user-centric selection problem arising from mobile edge computing, ridesharing applications, etc. In the proposed model, each arm is associated with discrete units of resources, each play is associate with movement costs and multiple plays can pull the same arm simultaneously. To learn the optimal action profile (an action profile prescribes the arm that each play pulls), there are two challenges: (1) the number of action profiles is large, i.e., M^K, where K and M denote the number of pla

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Lukowicz, Krzystof, and Artur Strzelecki. "User Satisfaction on Social Media Profile of E-sports Organization." Marketing and Management of Innovations, no. 4 (2020): 61–75. http://dx.doi.org/10.21272/mmi.2020.4-05.

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E-sport is one of the most rapidly growing branches of modern entertainment. Many factors influence this rapid progress such as easy access to the broadcast of matches, free e-sport games, or enjoying the favorite match are just a few of them. Moreover, the regularly growing number of tournaments organized (both online and hosted in the largest sports halls in the world) makes more and more older people interested in this phenomenon. Apart from the pure entertainment aspect, electronic sports offer great business opportunities. Proper use of social media allows generating high financial result

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Jayanthi, J., and M. Ezhilmathi. "Evaluating the Effectiveness of Web Search Metrics." Asian Journal of Computer Science and Technology 1, no. 2 (2012): 16–19. http://dx.doi.org/10.51983/ajcst-2012.1.2.1707.

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Software metrics are the key performance indicators, using which the performance of a system can be assessed quantitatively. Metrics can also be applied for personalized web search which can be used to retrieve relevant results for each individual user depending on their unique profile. Although personalized search based on user profile has been under research for many years and various metrics have been proposed, it is still uncertain whether personalization is unswervingly effective on different queries for different user profiles. We present a framework for personalized search which retriev

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Priporova, E. A., and E. R. Agadullina. "Social Motives for Using Social Networks: Analysis of User Groups." Social Psychology and Society 10, no. 4 (2019): 96–111. http://dx.doi.org/10.17759/sps.2019100407.

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The article describes various social motives for using social networks (maintaining and developing relationships, belongness to a particular group, and self-presentation). The results of the study showed that users of social networks (n = 579) can be divided into four different profiles depending on the degree of their motivation to use social networks (1 — moderate orientation to belongness and self-presentation; 2 — orientation towards main¬taining social relations ; 3 — low social motivation; 4 — high social motivation). The comparison of users from different profiles by their personality t

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Korepanova, Anastasiya A., Valerii D. Oliseenko, Maxim V. Abramov, and Alexander L. Tulupyev. "Application of Machine Learning Methods in the Task of Identifying User Accounts in Two Social Networks." Computer tools in education, no. 3 (September 30, 2019): 29–43. http://dx.doi.org/10.32603/2071-2340-2019-3-29-43.

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The article describes the approach to solving the problem of comparing user profiles of different social networks and identifying those that belong to one person. An appropriate method is proposed based on a comparison of the social environment and the values of account profile attributes in two different social networks. The results of applying various machine learning models to solving this problem are compared. The novelty of the approach lies in the proposed new combination of various methods and application to new social networks. The practical significance of the study is to automate the

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Muhammad, Asrori. "Professional Counselor Profile Analysis Based on Expert and User Expectations." Advances in Social Sciences Research Journal 10, no. 5 (2023): 122–30. http://dx.doi.org/10.14738/assrj.105.14695.

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The ultimate goal of the present research is to develop profiles and characteristics of professional counselors and their educational attainment as expected by experts and users so that standards for counselor education programs can be developed to produce professional counselor candidates. The specific objectives are (1) to describe the profile of a professional counselor having personal, social, and professional characteristics based on the expectations of experts and users; (2) to classify the sources of acquiring the profiles and characteristics expected by experts and users; and (3) to de

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Zabielski, Michał, Zbigniew Tarapata, and Rafał Kasprzyk. "Adaptive method of similarity detection of user profiles on online social networks." Bulletin of the Military University of Technology 68, no. 2 (2019): 43–57. http://dx.doi.org/10.5604/01.3001.0013.3002.

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The paper presents a method, based on graph and network theory, which allows to detect cloned user profiles on Online Social Networks. Moreover, an idea of similarity containers, which gives an opportunity to incorporate importance and context of data into a model, was introduced. The presented solutions were adapted to the idea of simulation environment, which will allow to detect a profile cloning process before that activity will be completely performed by an attacker. Keywords: Online Social Networks, user profile cloning, violation of privacy on the web.

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Preethi, I. "Dynamic User Profile Personalization in Web Mining." International Journal of Innovative Research in Applied Sciences and Engineering 1, no. 8 (2018): 170. http://dx.doi.org/10.29027/ijirase.v1.i8.2018.170-173.

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Wei, Jian Liang. "Finding Representative Tags for User Profile Construction." Advanced Materials Research 143-144 (October 2010): 399–403. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.399.

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Every resource in social tagging system have hundreds even thousands tags. To every certain resource, tags always have different popularity. The higher popularity a tag has, the more it suit for represent features of resource. This paper first find Top30 tags are popular tags, but the average tagging rate is quite low while approaching the 30th tag. Thus, six groups of resource that have vary saved times are taken for further analyzing. In all six groups, Top9 tags have high ATR, as well as ATR deviation, which mean these tags have obvious advantages while compare with others. Thus we take Top

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Adib, Jihad, Rachida Ait Abdelouahid, Abdelaziz Marzak, and Hicham Moutachaouik. "Ontological user profile for E-orientation platforms." Procedia Computer Science 198 (2022): 417–22. http://dx.doi.org/10.1016/j.procs.2021.12.263.

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Iguchi, Koichi, Yoshinori Hijikata, and Shogo Nishida. "TV program recommendation by individuating user profile." Transactions of the Japanese Society for Artificial Intelligence 30, no. 1 (2015): 71–83. http://dx.doi.org/10.1527/tjsai.30.71.

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Stanton, Jeffrey M. "Company profile of the frequent internet user." Communications of the ACM 45, no. 1 (2002): 55–59. http://dx.doi.org/10.1145/502269.502297.

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Xie, Haoran, Qing Li, Xudong Mao, Xiaodong Li, Yi Cai, and Yanghui Rao. "Community-aware user profile enrichment in folksonomy." Neural Networks 58 (October 2014): 111–21. http://dx.doi.org/10.1016/j.neunet.2014.05.009.

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Amo, Sandra de, Mouhamadou Saliou Diallo, Cheikh Talibouya Diop, Arnaud Giacometti, Dominique Li, and Arnaud Soulet. "Contextual preference mining for user profile construction." Information Systems 49 (April 2015): 182–99. http://dx.doi.org/10.1016/j.is.2014.11.009.

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ELALLIOUI, Youssouf, and Omar EL BEQQALI. "User profile Ontology for the Personalization approach." International Journal of Computer Applications 41, no. 4 (2012): 31–40. http://dx.doi.org/10.5120/5531-7577.

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Belarbi, Naima, Nadia Chafiq, Mohammed Talbi, Abdelwahed Namir, and Elhabib Benlahmar. "User Profiling in a SPOC: A method based on User Video Clickstream Analysis." International Journal of Emerging Technologies in Learning (iJET) 14, no. 01 (2019): 110. http://dx.doi.org/10.3991/ijet.v14i01.9091.

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In the present paper, we address to construct a structured user profile in a Small Private Online Course (SPOC) based on user’s video clickstream analysis. We adopt an implicit approach to infer user’s preferences and experience difficulty based on user’s video sequence viewing analysis at the click-level as Play, Pause, Move forward… the Bayesian method is used in order to infer implicitly user’s interests. Learners with similar clickstream behavior are then segmented into clusters by using the unsupervised K-Means clustering algorithm. Videos that could meet the individual learner interests

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Meghana,, T., J. V. B. S. Prem Sai, K. Deekshitha,, and A. Gnanesh Kumar. "Spammer Detection and Fake User Identification on Social Media." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42769.

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This paper presents about the detection of spammers and fake user accounts by using a machine learning model which is logistic regression using binary classification through a flask-based web application. The data set which is used for the training of the Machel learning model consist of 576 user profile characterized by 11 attributes which is presence of profile pic, username length, length of the full name of the user, user profile description length, presence of external URL’s, number of words in full name, is user name equals to full name, is user name public or private, number of follower

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Elachkar, I., H. Ouzif, and H. Labriji. "STRUCTURAL SIMILARITY MEASURE OF USERS PROFILES BASED ON A WEIGHTED BIPARTITE GRAPHS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W3-2020 (November 23, 2020): 203–7. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w3-2020-203-2020.

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Abstract. The user profile is a very important tool in several fields such as recommendation systems, customization systems etc., it is used to narrow the number of data or results provided for a specific user, also to minimize the cost and the time of processing of multiple systems. Whatever the user profile model used, it’s updating and enrichment is a very essential step in the information research process in order to obtain more interesting and satisfactory results, which lead the information systems to develop several techniques aiming to enrich them based especially on similarity methods

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Wang, Yaoxuan. "Research on User Profile and User Behavior of Integrating Big Data Platforms." Transactions on Economics, Business and Management Research 8 (August 8, 2024): 446–54. http://dx.doi.org/10.62051/3a6dex21.

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This paper discusses the construction and analysis method of user behavioral portrait by the data provided by the electric power platform in the big data environment. Firstly, it introduces the construction and analysis of user profiles based on big data platforms, which covers the construction of user basic attribute profiles, user behavioral characteristics profiles, user product characteristics profiles and user interaction characteristics profiles from different dimensions. Secondly, for the electric power sector, the article discusses the analysis of big data provided by electric power pl

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LI, XIN, and SHI-KUO CHANG. "USER PROFILING IN THE CHRONOBOT/VIRTUAL CLASSROOM SYSTEM." International Journal of Software Engineering and Knowledge Engineering 17, no. 02 (2007): 191–206. http://dx.doi.org/10.1142/s0218194007003185.

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The Chronobot/Virtual Classroom (CVC) system is a novel time knowledge exchange platform where any pair of users can exchange their time and knowledge. User profile that contains user attributes, preferences, and learning patterns serves as a primary basis to identify exchange partners and determine exchange rates. In this paper, we described the methodology to acquire knowledge about users i.e. user profile from their activities. The association between user profile and user behaviors (e.g. online reading, chatting and time/knowledge exchanging) is identified by several feedback indicators ex

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Herrera, Gail. "Google Scholar Users and User Behaviors: An Exploratory Study." College & Research Libraries 72, no. 4 (2011): 316–30. http://dx.doi.org/10.5860/crl-125rl.

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The University of Mississippi Library created a profile to provide linking from Google Scholar (GS) to library resources in 2005. Although Google Scholar does not provide usage statistics for institutions, use of Google Scholar is clearly evident in looking at library link resolver logs. The purpose of this project is to examine users of Google Scholar with existing data from interlibrary loan transactions and library Web site click-through logs and analytics. Questions about user status and discipline, as well as behaviors related to use of other library resources, are explored.

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Dalai, Niharika. "Single User-Item Profile Matrix in Recommendations System." Tuijin Jishu/Journal of Propulsion Technology 44, no. 3 (2023): 220–24. http://dx.doi.org/10.52783/tjjpt.v44.i3.260.

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Recommendation systems play a vital role in assisting users across various domains, including movies, music, books, and products, by providing personalized and relevant item suggestions. One popular approach employed in recommendation systems is the utilization of a utility matrix. This.0 matrix captures user-item interactions, with each cell representing a user's rating or preference for a particular item. By analyzing the utility matrix, recommendation systems can uncover patterns and resemblance between items and users, enabling accurate predictions and personalized recommendations. Collabo

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Kim, Jung-Han, Jang-Won Lee, Kyu-Heon Kim, and Doug-Young Suh. "User Profile Based Seamless Framework under HTTP Adaptive Streaming Environment." Journal of Broadcast Engineering 16, no. 1 (2011): 155–73. http://dx.doi.org/10.5909/jeb.2011.16.1.155.

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Sorensen, Humphrey, Adrian Riordan, and Colm Riordan. "Profiling with the INFOrmer Text Filtering Agent." JUCS - Journal of Universal Computer Science 3, no. (8) (1997): 988–1006. https://doi.org/10.3217/jucs-003-08-0988.

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INFOrmer is an intelligent filtering system, currently being applied to the management of USENET News articles. An individual may have one or more profiles, each representing a long-term interest of that user. The user profile is then used to measure the relevance of incoming articles and filter out irrelevant documents. A user profile may be modified as a result of relevance feedback, so that it adjusts to users changing interests. This paper discusses the architecture of INFOrmer and covers the profile/document representation and comparison techniques adopted within the system.

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Fedushko, S. S., and Yu O. Sierov. "Analysis of Functions and Data of Specialized Online Services for Forming a Professional Profile of a Web User." Visnyk of Kharkiv State Academy of Culture, no. 61 (June 29, 2022): 106–13. http://dx.doi.org/10.31516/2410-5333.061.10.

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The scientific topicality. For a modern scientist with progressive views and ambitious career and personal growth plans, it is critical to form a professional web profile and promote the own activities through specialized online services. Ukrainian scientists have actively used online services to form a reputation among foreign colleagues. The prospect of high-quality online communication between foreign partners has prompted web profiles creation in specialized online services. Web user profile data is crucial for finding business partners in Ukraine and abroad in science, sharing exper

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Viviani, Marco, Nadia Bennani, and Elöd Egyed-Zsigmond. "G-Profile." Information Resources Management Journal 25, no. 3 (2012): 61–77. http://dx.doi.org/10.4018/irmj.2012070103.

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In the digital world, many organizations are developing different applications (with different purposes) where users are generally represented by a heterogeneous set of attributes. From time to time, depending on the context, different attributes can provide different digital identities for the same user, often involved in the identification/authentication processes. In the personalized service provision perspective, the scope of identity management becomes much larger, and takes into account information susceptible to change such as user profile information as a whole. Many purely user-centri

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Bekkamov, Fayzi, and Yashin Sharifov. "EXTENDED USER PROFILING APPROACHES FOR RECOMMENDATION SYSTEMS." ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference 2 (June 22, 2024): 49–54. http://dx.doi.org/10.17770/etr2024vol2.8052.

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Currently, the volume of data in information systems and the information needs of users are increasing. This causes information overload and a number of difficulties in finding the necessary information. Therefore, individual approaches, including personalization of user profiles, are important in solving this problem. Creating a user profile is relevant for obtaining information from systems in accordance with the needs of the user and for personalizing the services provided by the system. The lack of direct user profiling in information systems creates a number of problems in providing perso

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