Learning user profiles from text in e-commerce

被引:0
作者
Degemmis, M [1 ]
Lops, P [1 ]
Ferilli, S [1 ]
Di Mauro, N [1 ]
Basile, TMA [1 ]
Semeraro, G [1 ]
机构
[1] Univ Bari, Dipartimento Informat, I-70125 Bari, Italy
来源
ADVANCED DATA MINING AND APPLICATIONS, PROCEEDINGS | 2005年 / 3584卷
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Exploring digital collections to find information relevant to a user's interests is a challenging task. Algorithms designed to solve this relevant information problem base their relevance computations on user profiles in which representations of the users' interests are maintained. This paper presents a new method, based on the classical Rocchio algorithm for text categorization, able to discover user preferences from the analysis of textual descriptions of items in online catalogues of ecommerce Web sites. Experiments have been carried out on a dataset of real users, and results have been compared with those obtained using an Inductive Logic Programming (ILP) approach and a probabilistic one.
引用
收藏
页码:370 / 381
页数:12
相关论文
共 15 条
[1]  
[Anonymous], VITAL STAT
[2]  
[Anonymous], P 5 ACM C DIG LIBR S
[3]  
Asnicar FA, 1997, P WORKSH AD SYST US, P3
[4]  
Billsus D, 1999, CISM COUR L, P99
[5]  
ESPOSITO F, 2003, P ECML PKDD 2003 1 E, P51
[6]  
Lieberman H, 1995, INT JOINT CONF ARTIF, P924
[7]  
Magnini B, 2001, LECT NOTES ARTIF INT, V2109, P74
[8]  
Mitchell TM., 1997, MACH LEARN, V1
[9]   Text-learning and related intelligent agents: A survey [J].
Mladenic, D .
IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1999, 14 (04) :44-54
[10]   Learning and revising user profiles: The identification of interesting Web sites [J].
Pazzani, M ;
Billsus, D .
MACHINE LEARNING, 1997, 27 (03) :313-331