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

Department of Artificial Intelligence and Data Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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.

Original language	English
Title of host publication	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
Editors	Jorg Roth, Jairo Gutierrez, Ajith P. Abraham
Publisher	IADIS Press
Pages	50-57
Number of pages	8
ISBN (Electronic)	9789728924409
Publication status	Published - 2020
Event	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 Duration: 3 Jul 2007 → 8 Jul 2007

Publication series

Name	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

Conference

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
Country/Territory	Portugal
City	Lisbon
Period	3/07/07 → 8/07/07

Bibliographical note

Publisher Copyright:
© 2007 IADIS

Funding

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

Funders	Funder number
TUBITAK	105E162
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

Keywords

Ant Colony Optimization
Recommender System
Web mining

Cite this

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. editor / 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).

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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",

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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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Demir, Gül Nildem

AU - Ögüdücü, Sule Gündüz

PY - 2020

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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.

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A2 - Gutierrez, Jairo

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PB - IADIS Press

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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, editors, 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

Abstract

Publication series

Conference

Bibliographical note

Funding

Keywords

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