In this paper, we detect ''innovative topics'', those that are new and hopefully interesting to the user. We try to expand user interests significantly by letting the user browse those topics. We first generate user-interest ontologies that allow user profiles to be constructed as a hierarchy of classes where a user interest weight is assigned to each class and instance. Next, we measure the similarity between user interests by using interest weights on their user-interest ontologies and generate user group GÜ that has high similarity to user u. The innovative topics for u are then detected by determining a suitable size of GÜ and analyzing the ontologies in GÜ.
Description
Detecting innovative topics based on user-interest ontology
%0 Journal Article
%1 nakatsuji2009detecting
%A Nakatsuji, Makoto
%A Yoshida, Makoto
%A Ishida, Toru
%C Amsterdam, The Netherlands, The Netherlands
%D 2009
%I Elsevier Science Publishers B. V.
%J Web Semant.
%K unread
%N 2
%P 107--120
%R http://dx.doi.org/10.1016/j.websem.2009.01.001
%T Detecting innovative topics based on user-interest ontology
%U http://portal.acm.org/citation.cfm?id=1540978&dl=GUIDE&coll=GUIDE&CFID=76254420&CFTOKEN=46420893
%V 7
%X In this paper, we detect ''innovative topics'', those that are new and hopefully interesting to the user. We try to expand user interests significantly by letting the user browse those topics. We first generate user-interest ontologies that allow user profiles to be constructed as a hierarchy of classes where a user interest weight is assigned to each class and instance. Next, we measure the similarity between user interests by using interest weights on their user-interest ontologies and generate user group GÜ that has high similarity to user u. The innovative topics for u are then detected by determining a suitable size of GÜ and analyzing the ontologies in GÜ.
@article{nakatsuji2009detecting,
abstract = {In this paper, we detect ''innovative topics'', those that are new and hopefully interesting to the user. We try to expand user interests significantly by letting the user browse those topics. We first generate user-interest ontologies that allow user profiles to be constructed as a hierarchy of classes where a user interest weight is assigned to each class and instance. Next, we measure the similarity between user interests by using interest weights on their user-interest ontologies and generate user group G"U that has high similarity to user u. The innovative topics for u are then detected by determining a suitable size of G"U and analyzing the ontologies in G"U.},
added-at = {2010-02-15T14:28:10.000+0100},
address = {Amsterdam, The Netherlands, The Netherlands},
author = {Nakatsuji, Makoto and Yoshida, Makoto and Ishida, Toru},
biburl = {https://www.bibsonomy.org/bibtex/20aaad816cddef4b5a996b00eb5afd87d/utahell},
description = {Detecting innovative topics based on user-interest ontology},
doi = {http://dx.doi.org/10.1016/j.websem.2009.01.001},
interhash = {050e25cd4724120c88de15bc8665e738},
intrahash = {0aaad816cddef4b5a996b00eb5afd87d},
issn = {1570-8268},
journal = {Web Semant.},
keywords = {unread},
number = 2,
pages = {107--120},
publisher = {Elsevier Science Publishers B. V.},
timestamp = {2010-02-15T14:28:10.000+0100},
title = {Detecting innovative topics based on user-interest ontology},
url = {http://portal.acm.org/citation.cfm?id=1540978&dl=GUIDE&coll=GUIDE&CFID=76254420&CFTOKEN=46420893},
volume = 7,
year = 2009
}