Log in

Relevant bibliographies by topics / User profile / Journal articles

Journal articles on the topic 'User profile'

To see the other types of publications on this topic, follow the link: User profile.

Author: Grafiati

Published: 4 June 2021

Last updated: 14 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'User profile.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

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 (June 30, 2011): 42–47. http://dx.doi.org/10.5120/2903-3808.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Grida, Mohamed, Lamiaa Fayed, and Mohamed Hassan. "User Profile: Theoretical Background." International Journal of Engineering Trends and Technology 68, no. 8 (August 25, 2020): 10–17. http://dx.doi.org/10.14445/22315381/ijett-v68i8p203s.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

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 (August 2010): 389–410. http://dx.doi.org/10.1142/s0218488510006611.

Full text

Abstract:

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 representation of a user profile is based on a structured model of user cognitive states, including a competence profile, a preference profile and an acquaintance profile. The strategy for deriving and updating profiles is to record the sequence of accessed resources by each user, and to update preference profiles accordingly, so as to suggest similar resources at next user accesses. The adaption of the preference profile is performed continuously, but in earlier stages it is more sensitive to updates (plastic phase) while in later stages it is less sensitive (stable phase) to allow resource recommendation. Simulation results are reported to show the effectiveness of the proposed approach.

APA, Harvard, Vancouver, ISO, and other styles

4

Petersen, Francoise, Giovanni Bartolomeo, and Mike Pluke. "Personalization and User Profile Management." International Journal of Interactive Mobile Technologies (iJIM) 2, no. 4 (September 30, 2008): 25. http://dx.doi.org/10.3991/ijim.v2i4.666.

Full text

Abstract:

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 Networks (NGN) and the convergence between telephony and Internet services offer a wide range of new terminal and service definition possibilities, and a much wider range of application in society. This paper describes the personalization and profile management activities at European Telecommunications Standards Institute (ETSI) Technical Committee Human Factors, together with relevant experimentations in recent European research projects.

APA, Harvard, Vancouver, ISO, and other styles

5

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.

Full text

Abstract:

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 using a Particle Swarm Optimization - based technique. We reveal interesting results in comparing with a standard user modeling approach.

APA, Harvard, Vancouver, ISO, and other styles

6

Eyharabide, Victoria, and Analía Amandi. "Ontology-based user profile learning." Applied Intelligence 36, no. 4 (June 3, 2011): 857–69. http://dx.doi.org/10.1007/s10489-011-0301-4.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

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.

Full text

Abstract:

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 propose a multiple user information user identification framework (MUIUI). Firstly, we develop multiprocess crawlers to obtain the user data from two popular social networks, Twitter and Facebook. Secondly, we use named entity recognition and entity linking to obtain and integrate locations and organizations from profiles and UGCs. We also extract URLs from profiles and UGCs. We apply the locations jointly with the relationships and develop several algorithms to measure the similarity of the display name, all locations, all organizations, location in profile, all URLs, following organizations, and user ID, respectively. Afterward, we propose a fusion classifier machine learning-based user identification method. The results show that the F1 score of MUIUI reaches 86.46% on the dataset. It proves that MUIUI can reduce the impact of user data that are missing or incomplete.

APA, Harvard, Vancouver, ISO, and other styles

8

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 (April 2016): 44–56. http://dx.doi.org/10.4018/ijisss.2016040104.

Full text

Abstract:

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 applications (E recruitment field).

APA, Harvard, Vancouver, ISO, and other styles

9

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 (September 30, 2016): 15–22. http://dx.doi.org/10.5121/ijmpict.2016.7302.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Kaya, Buket. "User Profile Based Paper Recommendation System." International Journal of Intelligent Systems and Applications in Engineering 2, no. 6 (June 29, 2018): 151–57. http://dx.doi.org/10.18201/ijisae.2018642079.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Pramiyati, Titin, Iping Supriana, and Ayu Purwarianti. "Pengenalan Entitas User Profile Pada Twitter." Jurnal INKOM 8, no. 2 (April 28, 2015): 103. http://dx.doi.org/10.14203/j.inkom.411.

Full text

Abstract:

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 karena itu, paper ini menjelaskan hasil proses pengenalan entitas yang dilakukan terhadap data yang terdapat pada user profile. Perangkat lunak yang digunakan untuk mengenali data sebagai entitas adalah IndonesiaNetagger. IndonesiaNettagger, merupakan perangkat lunak untuk mengenali entitas yang ditulis dalam bahasa Indonesia. Kami melakukan penelitian dalam empat tahap, yaitu pengenalan entity dengan data Bio twitter yang asli,identifikasi kesalahan proses pengenalan, formalisasi data dan pengujian pengenalan entitas akhir. Hasil penelitian menunjukkan keberhasilan sebagai berikut; entitas Person dikenali dengan benar adalah sebesar 71% dari total data entitas yang tersedia, entitas Organization dikenali dengan benar sebasar 50%, entitas Position 20% dikenali denganbenar, dan 50% entitas Location dikenali dengan benar.

APA, Harvard, Vancouver, ISO, and other styles

12

Schöggl-Ernst, Elisabeth. "The Change of User Profile in the Styrian Provincial Archives." Atlanti 26, no. 2 (October 25, 2016): 13–22. http://dx.doi.org/10.33700/2670-451x.26.2.13-22(2016).

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

13

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.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

14

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 (May 27, 2021): 1–27. http://dx.doi.org/10.1145/3457151.

Full text

Abstract:

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 customization of user interface according to the needs of diverse users, in this work we asses the suitability of a tool that customize web interfaces based on the needs and preferences of end users. UIFlex is a web-based browser plugin that enables users to define their interaction profile. In this task, users are supported by fifteen web-based design rules that were extracted from the literature and the knowledge of authorities. To customize the presentation of web interfaces, UIFlex relies on a set of rules defined for each individual user and "injects" JavaScript codes, Cascading Style Sheets (CSS) and in some cases HyperText Markup Language (HTML) codes in any page that follows W3C standards. UIFlex was evaluated by 104 users of diverse interaction profiles. The results obtained are promising and suggest that the solution improves the perception that the interactive system performs as desired by users.

APA, Harvard, Vancouver, ISO, and other styles

15

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 (July 18, 2016): 448–77. http://dx.doi.org/10.1108/ajim-06-2015-0091.

Full text

Abstract:

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 various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings – Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level. Originality/value – Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

APA, Harvard, Vancouver, ISO, and other styles

16

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.

Full text

Abstract:

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-UQP) framework is proposed. HFRS-UQP framework is split into two processes, where filtering and switching are carried out. The data mining based filtering in our research work uses the Hamilton Filtering framework to filter user result based on personalized information on automatic updated profiles through search engine. Maximized result is fetched, that is, filtered out with respect to user behavior profiles. The switching performs accurate filtering updated profiles using regime switching. The updating in profile change (i.e., switches) regime in HFRS-UQP framework identifies the second- and higher-order association of query result on the updated profiles. Experiment is conducted on factors such as personalized information search retrieval rate, filtering efficiency, and precision ratio.

APA, Harvard, Vancouver, ISO, and other styles

17

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

Full text

Abstract:

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-centric identity management systems has emerged in the few last years, among them the Higgins project that provides the user with a direct control over his/her data and covers some data security issues. However, a complete user-centric view of extended user identity management is not realistic, in our opinion. In this paper, the authors present G-Profile: a hybrid, open, general-purpose and flexible user modeling system for extended identity management in multi-application environments. G-Profile also tackles the trade-off between users’ and applications’ requirements.

APA, Harvard, Vancouver, ISO, and other styles

18

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 (December 6, 2020): 211–19. http://dx.doi.org/10.21456/vol10iss2pp211-219.

Full text

Abstract:

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 determining the user profile. The weights of the criteria and alternatives for profile users are acquired through the dissemination of questionnaires to 117 respondents. In the meantime, parameters such as Random-Access Memory (RAM), Read-Only Memory (ROM), camera, processor, screen, and battery are added to the smartphone list of criteria upon on the interviews of 15 experts and practices in smartphone and Information Technology (IT). F-AHP rates each of the Smartphone and User Profiles as a first-round output. A rule-based expert system is employed to intertwine Smartphone and User Profiles decision-making viewpoints. The relationship between the Smartphone and the User Profile is therefore circumscribed as the final decision to applaud the acceptable Smartphone for those users of the profile. A prototype of the MatchSmartPhone application has been developed to computerize the F-AHP calculation. This application can be used to assist users according to the user's profile in delivering the best Smartphone device recommendations. Users would be wiser and smarter when shopping in advance.

APA, Harvard, Vancouver, ISO, and other styles

19

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.

Full text

Abstract:

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 results for investors. The paper is dedicated to the user’s satisfaction from using social media profiles of e-sport organizations, teams, and players. The research covers the basic information about e-sport, social media, and e-marketing forms on social media for e-sport organizations. This work aims to assess the factors influencing the feeling of satisfaction with the use of the social media profile. The purpose of this study is to investigate the influence of Perceived Profile Usefulness, Perceived Entertainment, Identification with Organization and Players, and satisfaction on users’ Intention to Follow and Recommend social media profile of e-sport organization. The study tested and used the model in the context of social media profiles. The partial least square method of structural equation modeling is employed to test the proposed research model. The study utilizes an online survey to obtain data from 209 Polish e-sport enthusiasts (both players and spectators). The data set was analyzed using SmartPLS 3 software. The obtained results showed that the best predictor of users’ Satisfaction is Integration with Organization and Players, followed by Perceived Entertainment. Satisfaction predicts users’ Intention to Follow and Recommend the social media profile of the e-sport organization. The findings improve understanding regarding the marketing actions in e-sport’s social media profiles, and this work is therefore of particular interest to e-sport organizations, e-sport teams, and e-sport players. Keywords: E-sport, social media profile, satisfaction, computer games, social media marketing.

APA, Harvard, Vancouver, ISO, and other styles

20

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

Full text

Abstract:

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 (IBL) algorithm that assigns weights to feature values and considers these weights for the clustering. Three feature weight methods are proposed for the MDC and, all three, have been tested and evaluated. Simulations were conducted with using two sets of user profile datasets, which are the training (includes 10,000 instances) and test (includes 1000 instances) datasets. These datasets reflect each user’s personal information, preferences and interests. Additional simulations and comparisons with existing weighted and non-weighted instance-based algorithms were carried out in order to demonstrate the performance of proposed algorithm. Experimental results using the user profile datasets demonstrate that the proposed algorithm has better clustering accuracy performance compared to other algorithms. This work is based on the doctoral thesis of the corresponding author.

APA, Harvard, Vancouver, ISO, and other styles

21

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

Full text

Abstract:

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 innovative model for user profiling. The innovation is based on the enrichment of common user profiling architectures to include location and other contextual attributes, so that enhanced adaptability and personalization can be achieved. For each location and context instance an associated User Profile instance is created and hence, service provisioning is adapted to the User Profile instance that better apply to the current context. The generic model, the structure and the content of this location- and context-sensitive User Profile, along with some related implementation issues, are discussed.

APA, Harvard, Vancouver, ISO, and other styles

22

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 (June 28, 2022): 6231–38. http://dx.doi.org/10.1609/aaai.v36i6.20572.

Full text

Abstract:

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 plays and arms respectively; (2) feedbacks on action profiles are not available, but instead feedbacks on some model parameters can be observed. To address the first challenge, we formulate a completed weighted bipartite graph to capture key factors of the offline decision problem with given model parameters. We identify the correspondence between action profiles and a special class of matchings of the graph. We also identify a dominance structure of this class of matchings. This correspondence and dominance structure enable us to design an algorithm named OffOptActPrf to locate the optimal action efficiently. To address the second challenge, we design an OnLinActPrf algorithm. We design estimators for model parameters and use these estimators to design a Quasi-UCB index for each action profile. The OnLinActPrf uses OffOptActPrf as a subroutine to select the action profile with the largest Quasi-UCB index. We conduct extensive experiments to validate the efficiency of OnLinActPrf.

APA, Harvard, Vancouver, ISO, and other styles

23

Biswas, Pooshpanjan Roy, Alessandro Beltrami, and Joan Saez Gomez. "A testing paradigm for quantifying ICC profilers." Color and Imaging Conference 2019, no. 1 (October 21, 2019): 80–85. http://dx.doi.org/10.2352/issn.2169-2629.2019.27.15.

Full text

Abstract:

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 for color accuracy, vivid colors or pleasing reproduction of images. Using the same decisions on different profile engines, the final visual output can look different (more than one Just Noticeable Difference[16]) depending on the profile engine used and the color algorithms that they implement. Profile performance substantially depends on the profiler engine used to create them. Different profilers provide the user with varying levels of liberty to design a profile for their color management needs and preference. The motivation of this study is to rank the performance of various market leading profiler engines on the basis of different metrics designed specifically to report the performance of particular aspects of these profiles. The study helped us take valuable decisions regarding profile performance without any visual assessment to decide on the best profiler engine.

APA, Harvard, Vancouver, ISO, and other styles

24

Preethi, I. "Dynamic User Profile Personalization in Web Mining." International Journal of Innovative Research in Applied Sciences and Engineering 1, no. 8 (February 18, 2018): 170. http://dx.doi.org/10.29027/ijirase.v1.i8.2018.170-173.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

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.

Full text

Abstract:

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 Top9 as representative tags. Finally, a user profile construction algorithm is given out based on representative tags.

APA, Harvard, Vancouver, ISO, and other styles

26

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

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

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

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.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

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

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

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 (January 30, 2011): 155–73. http://dx.doi.org/10.5909/jeb.2011.16.1.155.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

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.

Full text

Abstract:

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 traits and online behavior showed that users with high social motivation demonstrate the higher level of extraversion, agree¬ableness, and openness to experience compared with individuals from other profiles. Users from the “orientation towards maintaining social relations” profile do not differ from users with low social motivation in terms of the level of agreeableness and openness to experience, and users from the profile “moderate orientation to belongness and self-presentation” do not differ from users with high motivation regarding the level of neuroticism and openness to experience. In general, respondents from the profile with high social motivation demonstrate the most intensive use of social networks for all behavioral parameters. The smallest differences in behavior in the social networks are observed between respondents from the profiles “orientation towards maintaining social relations” and “low social motivation,’’ as well as “moderate orientation to belongness and self-presentation” and “high social motivation”.

APA, Harvard, Vancouver, ISO, and other styles

34

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.

Full text

Abstract:

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 between user profiles. The similarity methods are used for several tasks such as the detection of duplicate profiles in online social network, also to answer the problem of cold start, and to predict users who can become friends as well as their future intentions, etc. In this paper, we propose a new approach to express the similarity between users profiles by developing a structural similarity measure to calculate the similarity between user profiles based on SimRank measure or similarity ,and the properties of bipartite graphs, in order to take advantage of the information provided by the relational structure between user profiles and their interests, our method is characterized by the similarity propagation between graph's nodes over iterations from source nodes to their successors, so our method finds profiles similar to the query profile, whether the links are direct or indirect between profiles.

APA, Harvard, Vancouver, ISO, and other styles

35

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 (January 17, 2019): 110. http://dx.doi.org/10.3991/ijet.v14i01.9091.

Full text

Abstract:

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 and offer a best and personalized experienced learning can therefore be recommended for a learner while enrolling in a SPOC based on his videos interactions and exploiting similar learners’ profiles.

APA, Harvard, Vancouver, ISO, and other styles

36

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.

Full text

Abstract:

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 process of determining the ownership of profiles in various social networks to one user. These results can be applied in the task of constructing a meta-profile of a user of an information system for the subsequent construction of a profile of his vulnerabilities, as well as in other studies devoted to social networks.

APA, Harvard, Vancouver, ISO, and other styles

37

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 (June 28, 2019): 43–57. http://dx.doi.org/10.5604/01.3001.0013.3002.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

38

Herrera, Gail. "Google Scholar Users and User Behaviors: An Exploratory Study." College & Research Libraries 72, no. 4 (July 1, 2011): 316–30. http://dx.doi.org/10.5860/crl-125rl.

Full text

Abstract:

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.

APA, Harvard, Vancouver, ISO, and other styles

39

OKUBO, Kazunori, Yoshinori HIJIKATA, and Shogo NISHIDA. "An Empirical Study of User Awareness by Visualizing User Profile for Information Recommendation." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 25, no. 1 (2013): 511–23. http://dx.doi.org/10.3156/jsoft.25.511.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Singh, Sarabdeep, Michael Shepherd Corresponding Author, Jack Duffy, and Carolyn Watters. "An adaptive user profile for filtering news based on a user interest hierarchy." Proceedings of the American Society for Information Science and Technology 43, no. 1 (October 10, 2007): 1–21. http://dx.doi.org/10.1002/meet.1450430154.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

He, Yu Yang, and Yan Tang. "Research of User Profile Model in Personalized Search." Applied Mechanics and Materials 543-547 (March 2014): 3364–68. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.3364.

Full text

Abstract:

For personalized service, existing user interest model primarily through the select weights Highest N keywords to represent the user interest model based on space vector method. The method of establishing the model is tend to content-based analysis methods and there is a serious "cold start" problem, cannot meet the demand for personalized services. Therefore, this paper add collaborative filtering factor in the process of establishing user interest model, and verified by experiment, after adding personalization features which make the service more obvious. In a certain extent, solve the new user's "cold start" problem.

APA, Harvard, Vancouver, ISO, and other styles

42

Kuppusamy, K. S. "A Multimodal Approach to Incremental User Profile Building." International journal of Web & Semantic Technology 3, no. 4 (October 31, 2012): 43–53. http://dx.doi.org/10.5121/ijwest.2012.3405.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Yoon, Sung Hee. "Personalized Web Search using Query based User Profile." Journal of the Korea Academia-Industrial cooperation Society 17, no. 2 (February 29, 2016): 690–96. http://dx.doi.org/10.5762/kais.2016.17.2.690.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Hussain, Saba M., and Ghaidaa A. Al-Sultany r. "Enhancing Mole Trust Algorithm Based Analysis User Profile." Journal of Physics: Conference Series 1530 (May 2020): 012157. http://dx.doi.org/10.1088/1742-6596/1530/1/012157.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Shao, Jingfeng. "A Fuzzy Ontology Framework Based on User Profile." Education Journal 6, no. 5 (2017): 152. http://dx.doi.org/10.11648/j.edu.20170605.12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Yi, Xun, Elisa Bertino, Fang-Yu Rao, Kwok-Yan Lam, Surya Nepal, and Athman Bouguettaya. "Privacy-Preserving User Profile Matching in Social Networks." IEEE Transactions on Knowledge and Data Engineering 32, no. 8 (August 1, 2020): 1572–85. http://dx.doi.org/10.1109/tkde.2019.2912748.

Full text

APA, Harvard, Vancouver, ISO, and other styles

47

Eleftheriadis, G. P., and M. E. Theologou. "User profile identification in future mobile telecommunications systems." IEEE Network 8, no. 5 (September 1994): 33–39. http://dx.doi.org/10.1109/65.313012.

Full text

APA, Harvard, Vancouver, ISO, and other styles

48

Kurzke, Christian, Michael Galle, and Manfred Bathelt. "WebAssist: a user profile specific information retrieval assistant." Computer Networks and ISDN Systems 30, no. 1-7 (April 1998): 654–55. http://dx.doi.org/10.1016/s0169-7552(98)00092-0.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Alaoui, Sara, Younès EL Bouzekri EL Idrissi, and Rachida Ajhoun. "Building Rich User Profile Based on Intentional Perspective." Procedia Computer Science 73 (2015): 342–49. http://dx.doi.org/10.1016/j.procs.2015.12.002.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Vorbeck-Meister, I., A. Hassl, F. Vorbeck, and M. Rotter. "Internet user profile in the field of parasitology." Parasitology Research 87, no. 1 (January 1, 2001): 7–13. http://dx.doi.org/10.1007/s004360000285.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!