Content-based Filtering with Tags: the FIRSt System

被引：2

作者：

Lops, Pasquale ^{[1
]}

de Gemmis, Marco ^{[1
]}

Semeraro, Giovanni ^{[1
]}

Gissi, Paolo ^{[1
]}

Musto, Cataldo ^{[1
]}

Narducci, Fedelucio ^{[1
]}

机构：

[1] Univ Bari Aldo Morof, Dept Comp Sci, I-70126 Bari, Italy

来源：

2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS | 2009年

关键词：

Web; 2.0; Information Filtering; User Modeling; Recommender Systems;

D O I：

10.1109/ISDA.2009.84

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Basic content personalization consists in matching up the attributes of a user profile, in which preferences and interests are stored, against the attributes of a content object. This paper describes a content-based recommender system, called FIRSt, that integrates user generated content (UGC) with semantic analysis of content. The main contribution of FIRSt is an integrated strategy that enables a content-based recommender to infer user interests by applying machine learning techniques, both on official item descriptions provided by a publisher and on freely keywords which users adopt to annotate relevant items. Static content and dynamic content are preventively analyzed by advanced linguistic techniques in order to capture the semantics of the user interests, often hidden behind keywords. The proposed approach has been evaluated in the domain of cultural heritage personalization.

引用

页码：255 / 260

页数：6

共 50 条

[31] Learning user interest model for content-based filtering in personalized recommendation system
Gong, Songjie
International Journal of Digital Content Technology and its Applications, 2012, 6 (11) : 155 - 162
[32] Comparison between Content-Based and Collaborative Filtering Recommendation System for Movie Suggestions
Ariff, Noratiqah Mohd
Abu Bakar, Mohd Aftar
Rahim, Nurul Farhanah
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICS, ENGINEERING AND INDUSTRIAL APPLICATIONS 2018 (ICOMEIA 2018), 2018, 2013
[33] Query optimization method based on automaton for content-based filtering
Wang, Tong
Liu, Daxin
Lin, Xuanzuo
20TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS, VOL 2, PROCEEDINGS, 2006, : 724 - +
[34] Content-based filtering for music recommendation based on ubiquitous computing
Kim, Jong-Hun
Kang, Un-Gu
Lee, Jung-Hyun
INTELLIGENT INFORMATION PROCESSING III, 2006, 228 : 463 - +
[35] The content-based VOD system
Jia, ZT
Li, LJ
He, GM
DCABES 2001 PROCEEDINGS, 2001, : 75 - 79
[36] Content-Based Network Filtering of Encrypted Image Data
Hamdi, Mohamed
Boudriga, Noureddine
2010 IEEE INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND INFORMATION SECURITY (WCNIS), VOL 1, 2010, : 343 - 348
[37] Content-based Approach for Vietnamese Spam SMS Filtering
Pham, Thai-Hoang
Le-Hong, Phuong
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP), 2016, : 41 - 44
[38] Content-based audio retrieval based on Gabor wavelet filtering
Lin, RS
Chen, LH
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2005, 19 (06) : 823 - 837
[39] Content-based Image Retrieval using Gabor Filtering
Barbu, Tudor
PROCEEDINGS OF THE 20TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATION, 2009, : 236 - 240
[40] Content-based text classiriers for pornographic web filtering
Polpinij, Jantima
Chotthanom, Anirut
Sibunruang, Chumsak
Chamchong, Rapeepom
Puangpronpitag, Somnuk
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, 2006, : 1481 - +

← 1 2 3 4 5 →