User Profiling for University Recommender System using Automatic Information Retrieval

被引:10
|
作者
Kanoje, Sumitkumar [1 ]
Mukhopadhyay, Debajyoti [1 ]
Girase, Sheetal [1 ]
机构
[1] MIT Pune, Dept Informat Technol, Pune 38, Maharashtra, India
关键词
User Profiling; Information Retrieval; Data Mining;
D O I
10.1016/j.procs.2016.02.002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
User Profiling is the process of Extracting, Integrating and Identifying the keyword based information to generate a structured Profile and then visualizing the knowledge out of these findings. User profiling helps personalizing a system to work according to user. Therefore user profiling or personalization is one of the major concepts used for accessing the user relevant information, which can be used to solve the difficult problems of recommender system like classification and ranking of items in accordance with an individual's interest. In this paper we focus on the problem of user profiling in which we aim at finding, extracting and integrating keyword based information from various web sources to generate a structured profile. Further we do some experiments on the profiled information to generate knowledge out of it. (C) 2016 The Authors. Published by Elsevier B.V.
引用
收藏
页码:5 / 12
页数:8
相关论文
共 50 条
  • [41] AUTOMATIC INDEXING IN A NITROGEN PRODUCTION INFORMATION RETRIEVAL SYSTEM
    FRANTS, YI
    VOISKUNSKII, VG
    MUKOSEI, VI
    FRANTS, VI
    NAUCHNO-TEKHNICHESKAYA INFORMATSIYA SERIYA 2-INFORMATSIONNYE PROTSESSY I SISTEMY, 1971, (04): : 15 - +
  • [42] A Collaborative Recommender Based on User Information and Item Information
    Gong, SongJie
    ISIP: 2009 INTERNATIONAL SYMPOSIUM ON INFORMATION PROCESSING, PROCEEDINGS, 2009, : 1 - 4
  • [43] A Bayesian Recommender Model for User Rating and Review Profiling
    Jiang, Mingming
    Song, Dandan
    Liao, Lejian
    Zhu, Feida
    TSINGHUA SCIENCE AND TECHNOLOGY, 2015, 20 (06) : 634 - 643
  • [44] Collective Knowledge Ontology User Profiling for Twitter Automatic User Profiling
    Pena, Paula
    del Hoyo, Rafael
    Vea-Murguia, Jorge
    Gonzalez, Carlos
    Mayo, Sergio
    2013 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCES ON WEB INTELLIGENCE (WI) AND INTELLIGENT AGENT TECHNOLOGIES (IAT), VOL 1, 2013, : 439 - 444
  • [45] Efficient User Profiling Based Intelligent Travel Recommender System for Individual and Group of Users
    R. Logesh
    V. Subramaniyaswamy
    V. Vijayakumar
    Xiong Li
    Mobile Networks and Applications, 2019, 24 : 1018 - 1033
  • [46] Efficient User Profiling Based Intelligent Travel Recommender System for Individual and Group of Users
    Logesh, R.
    Subramaniyaswamy, V.
    Vijayakumar, V.
    Li, Xiong
    MOBILE NETWORKS & APPLICATIONS, 2019, 24 (03): : 1018 - 1033
  • [47] A Bayesian Recommender Model for User Rating and Review Profiling
    Mingming Jiang
    Dandan Song
    Lejian Liao
    Feida Zhu
    Tsinghua Science and Technology, 2015, 20 (06) : 634 - 643
  • [48] A quality based recommender system to disseminate information in a university digital library
    Tejeda-Lorente, Alvaro
    Porcel, Carlos
    Peis, Eduardo
    Sanz, Rosa
    Herrera-Viedma, Enrique
    INFORMATION SCIENCES, 2014, 261 : 52 - 69
  • [49] Quantum Computing for Information Retrieval and Recommender Systems
    Dacrema, Maurizio Ferrari
    Pasin, Andrea
    Cremonesi, Paolo
    Ferro, Nicola
    ADVANCES IN INFORMATION RETRIEVAL, ECIR 2024, PT V, 2024, 14612 : 358 - 362
  • [50] Information Retrieval and Folksonomies together for Recommender Systems
    Chevalier, Max
    Dattolo, Antonina
    Hubert, Gilles
    Pitassi, Emanuela
    E-COMMERCE AND WEB TECHNOLOGIES, 2011, 85 : 172 - +