A web recommender system based on ant colony optimization

Murat Göksedef; Gül Nildem Demir; Sule Gündüz Ögüdücü

A web recommender system based on ant colony optimization

Murat Göksedef, Gül Nildem Demir, Sule Gündüz Ögüdücü

Yapay Zeka ve Veri Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

The rapid growth of Internet has caused an increase in the amount of web pages. Even a small web site consists of thousands of web pages and it becomes an important issue to guide the user to that contents she is or may be interested in. Thus, predicting the interest of a user and using this information to make recommendations has gained importance. Previously proposed methods for recommendation use data collected over time in order to recommend pages to new Web users. However, they do not assess the recommendations made by the system to develop the system further. In this paper, we present a new recommendation model for Web users which considers the behavior of new Web users. Our recommendation model combines the Click-Stream Tree Model with a method that is inspired by the Ant Colony Optimization method. Thus, our model is capable of learning new users' behaviors. The experimental results show that our model yields an improvement of the prediction accuracy.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007
Editörler	Jorg Roth, Jairo Gutierrez, Ajith P. Abraham
Yayınlayan	IADIS Press
Sayfalar	50-57
Sayfa sayısı	8
ISBN (Elektronik)	9789728924409
Yayın durumu	Yayınlandı - 2020
Etkinlik	2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007 - Lisbon, Portugal Süre: 3 Tem 2007 → 8 Tem 2007

Yayın serisi

Adı	MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007
Ülke/Bölge	Portugal
Şehir	Lisbon
Periyot	3/07/07 → 8/07/07

Bibliyografik not

Publisher Copyright:
© 2007 IADIS

Finansman

The authors were supported by the Scientific and Technological Research Council of Turkey (TUBITAK) EEEAG project 105E162.

Finansörler	Finansör numarası
TUBITAK	105E162
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Göksedef, M., Demir, G. N., & Ögüdücü, S. G. (2020). A web recommender system based on ant colony optimization. In J. Roth, J. Gutierrez, & A. P. Abraham (Eds.), MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007 (pp. 50-57). (MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007). IADIS Press.

Göksedef, Murat ; Demir, Gül Nildem ; Ögüdücü, Sule Gündüz. / A web recommender system based on ant colony optimization. MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007. editör / Jorg Roth ; Jairo Gutierrez ; Ajith P. Abraham. IADIS Press, 2020. pp. 50-57 (MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007).

@inproceedings{4c17e3fa9ed74d11b11335c51edafc31,

title = "A web recommender system based on ant colony optimization",

abstract = "The rapid growth of Internet has caused an increase in the amount of web pages. Even a small web site consists of thousands of web pages and it becomes an important issue to guide the user to that contents she is or may be interested in. Thus, predicting the interest of a user and using this information to make recommendations has gained importance. Previously proposed methods for recommendation use data collected over time in order to recommend pages to new Web users. However, they do not assess the recommendations made by the system to develop the system further. In this paper, we present a new recommendation model for Web users which considers the behavior of new Web users. Our recommendation model combines the Click-Stream Tree Model with a method that is inspired by the Ant Colony Optimization method. Thus, our model is capable of learning new users' behaviors. The experimental results show that our model yields an improvement of the prediction accuracy.",

keywords = "Ant Colony Optimization, Recommender System, Web mining",

author = "Murat G{\"o}ksedef and Demir, {G{\"u}l Nildem} and {\"O}g{\"u}d{\"u}c{\"u}, {Sule G{\"u}nd{\"u}z}",

note = "Publisher Copyright: {\textcopyright} 2007 IADIS; 2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007 ; Conference date: 03-07-2007 Through 08-07-2007",

year = "2020",

language = "English",

series = "MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007",

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}

Göksedef, M, Demir, GN & Ögüdücü, SG 2020, A web recommender system based on ant colony optimization. in J Roth, J Gutierrez & AP Abraham (eds), MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007. MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007, IADIS Press, pp. 50-57, 2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007, Lisbon, Portugal, 3/07/07.

A web recommender system based on ant colony optimization. / Göksedef, Murat; Demir, Gül Nildem; Ögüdücü, Sule Gündüz.
MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007. ed. / Jorg Roth; Jairo Gutierrez; Ajith P. Abraham. IADIS Press, 2020. p. 50-57 (MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - A web recommender system based on ant colony optimization

AU - Göksedef, Murat

AU - Demir, Gül Nildem

AU - Ögüdücü, Sule Gündüz

PY - 2020

Y1 - 2020

N2 - The rapid growth of Internet has caused an increase in the amount of web pages. Even a small web site consists of thousands of web pages and it becomes an important issue to guide the user to that contents she is or may be interested in. Thus, predicting the interest of a user and using this information to make recommendations has gained importance. Previously proposed methods for recommendation use data collected over time in order to recommend pages to new Web users. However, they do not assess the recommendations made by the system to develop the system further. In this paper, we present a new recommendation model for Web users which considers the behavior of new Web users. Our recommendation model combines the Click-Stream Tree Model with a method that is inspired by the Ant Colony Optimization method. Thus, our model is capable of learning new users' behaviors. The experimental results show that our model yields an improvement of the prediction accuracy.

AB - The rapid growth of Internet has caused an increase in the amount of web pages. Even a small web site consists of thousands of web pages and it becomes an important issue to guide the user to that contents she is or may be interested in. Thus, predicting the interest of a user and using this information to make recommendations has gained importance. Previously proposed methods for recommendation use data collected over time in order to recommend pages to new Web users. However, they do not assess the recommendations made by the system to develop the system further. In this paper, we present a new recommendation model for Web users which considers the behavior of new Web users. Our recommendation model combines the Click-Stream Tree Model with a method that is inspired by the Ant Colony Optimization method. Thus, our model is capable of learning new users' behaviors. The experimental results show that our model yields an improvement of the prediction accuracy.

KW - Ant Colony Optimization

KW - Recommender System

KW - Web mining

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M3 - Conference contribution

AN - SCOPUS:85090715894

T3 - MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007

SP - 50

EP - 57

BT - MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007

A2 - Roth, Jorg

A2 - Gutierrez, Jairo

A2 - Abraham, Ajith P.

PB - IADIS Press

T2 - 2007 IADIS European Conference on Data Mining, DM 2007, part of the 1st IADIS Multi Conference on Computer Science and Information Systems, MCCSIS 2007

Y2 - 3 July 2007 through 8 July 2007

ER -

Göksedef M, Demir GN, Ögüdücü SG. A web recommender system based on ant colony optimization. In Roth J, Gutierrez J, Abraham AP, editörler, MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007. IADIS Press. 2020. p. 50-57. (MCCSIS 2007 - IADIS Multi Conference on Computer Science and Information Systems - Proceedings of Wireless Applications and Computing 2007, Telecommunications, Networks and Systems 2007 and Data Mining 2007).

A web recommender system based on ant colony optimization

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Finansman

Diğer Dosyalar ve Linkler

Parmak izi

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