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Web page classification based on k-nearest neighbor approach

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Jong-Hyeok LeeAuthors Info & Claims

IRAL '00: Proceedings of the fifth international workshop on on Information retrieval with Asian languages

Pages 9 - 15

https://doi.org/10.1145/355214.355216

Published: 01 November 2000 Publication History

Abstract

Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web. In this paper, we propose a Web page classifier based on an adaptation of k-Nearest Neighbor (k-NN) approach. To improve the performance of k-NN approach, we supplement k-NN approach with a feature selection method and a term-weighting scheme using markup tags, and reform document-document similarity measure used in vector space model. In our experiments on a Korean commercial Web directory, our proposed methods in k-NN approach for Web page classification improved the performance of classification.

References

[1]

Andrew McCallum and Kamal Nigam, "A Comparison of Event Models for Naive Bayes Text Classification," In AAAI-98 Workshop on Learning for Text Categorization, 1998. http ://www.cs.cmu.edu/~mccallum.

[2]

Brij Masand, Gordon Linoff and David Waltz, "Classifying News Stories using Memory Based Reasoning," In Proceedings of the 15 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'92), pp. 59-65, Copenhagen, Denmark, 1992.

Digital Library

[3]

Chidanand Apt6 and Fred Damerau, "Automated Learning of Decision Rules for Text Categorization," ACM Transactions on Information Systems, Vol. 12, No. 3, pp. 233-251, 1994.

Digital Library

[4]

C.J. Van Rijsbergen, "A Theoretical Basis for the Use of Co-occurrence Data in Information Retrieval," Journal of Documentation, Vol. 33, No. 2, pp. 106- 119, June 1977.

[5]

David D. Lewis, "Representation and Learning in Information Retrieval," PhD thesis, Department of Computer Science; Univ. of Massachusetts; Amherst, MA 01003, 1992.

Digital Library

[6]

David D. Lewis, "An Evaluation of Phrasal and Clustered Representations on a Task", In Proceedings of the 15 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'92), pp. 37-50, Copenhagen, Denmark, 1992.

Digital Library

[7]

David D. Lewis and Marc Ringuette, "A comparison of two learning algorithms for text categorization," In Proceedings of the 3rd Annual Symposium on Document Analysis and Information Retrieval (SDAIR'94), University of Nevada, Las Vegas, USA, pp. 81-93, 1994.

[8]

G. Salton, "Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer," Addison-Weseley, Reading, Massachusetts, 1989.

Digital Library

[9]

L. Douglas Baker and Andrew Kachites McCallum, "Distributional Clustering of Word for Text Classification," In Proceedings of the 21 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'98), Melbourne, Australia, pp. 96-103, 1998.

Digital Library

[10]

Leah Larkey and W. Bruce Croft, "Combining Classifiers in Text Categorization," In Proceedings of the 19 th International Conference on Research and Development in Information Retrieval (SIGIR '96), pp. 289-297, Zurich, Switzerland, 1996

Digital Library

[11]

Makoto Iwayama and Takenobu Tokunaga, "Cluster- Based Text Categorization: A Comparison of Category Search Strategies," In Proceedings of the 18 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'95), pp. 273-280, Seattle, Washington, USA, 1995.

Digital Library

[12]

Oh-Woog Kwon, Sung-Hwa Jung, Jong-Hyeok Lee, and Geunbae Lee, "Evaluation of Category Features and Text Structural Information on a Text Categorization Using Memory Based Reasoning," In Proceedings of the 18 th International Conference on Computer Processing of Oriental Languages (ICCPOL'99), pp. 153-158, University of Tokushim, Japan, 1999.

[13]

Susan Dumais, John Platt, David Heckerman, and Mehran Sahami, "Inductive Learning Algorithms and Representations for Text Categorization," In Proceedings of the 7 th International Conference on Information and Knowledge Management (CIKM'98), 1998, http ://robotics.stanford.edu/users/sahami/papers.html.

Digital Library

[14]

Thorsten Joachims, "Text Categorization with Support Vector Machine: Learning with Many Relevant Feature," In Proceedings of European Conference on Machine Learning (ECML), 1998, http://www-ai.cs.unidortmund.de/PERSONAL/joachims.eng.html.

Digital Library

[15]

Thorsten Joachims, "Transductive Inference for Text Classification using Support Vector Machines," In Proceedings of International Conference on Machine Learning (ICML), 1999, http://www-ai.cs.unidortmund.de/PERSONAL/j oachims.eng.html.

Digital Library

[16]

Yiming Yang, "Expert Network: Effective and Efficient Learning from Human Decision in Text Categorization and Retrieval," In Proceedings of the 17 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'94), pp. 13-22, Dublin, Ireland, 1994.

Digital Library

[17]

Yiming Yang, "An Evaluation of Statistical Approach to Text Categorization," Information Retrieval, Vol. 1, No. 1/2, pp. 69-90, 1999.

Digital Library

[18]

Yiming Yang, and Xin Lui, "A Re-examination of Text Categorization Methods," In Proceedings of the 22 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'99), pp. 42-49, University of California, Berkeley, USA, 1999.

Digital Library

[19]

Wai Lam and Chao Yang Ho, "Using A Generalized Instance Set for Automatic Text Categorization," In Proceedings of the 21 th Annual International Conference on Research and Development in Information Retrieval (SIGIR'98), Melbourne, Australia, pp. 81-89, 1998.

Digital Library

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Web page classification based on k-nearest neighbor approach

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Published In

cover image ACM Conferences

IRAL '00: Proceedings of the fifth international workshop on on Information retrieval with Asian languages

November 2000

220 pages

ISBN:1581133006

DOI:10.1145/355214

Chairmen:
Kam-Fai Wong
Chinese Univ. of Hong Kong, Hong Kong, China
,
Dik L. Lee
Hong Kong Univ. of Science and Technology, Hong Kong, China
,
Jong-Hyeok Lee
Pohang Univ. of Science and Technology, Korea

Copyright © 2000 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
ACM Hong Kong Chapter: ACM Hong Kong Chapter Executive Committee
SIGIR: ACM Special Interest Group on Information Retrieval
SIGLINK: Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 November 2000

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IRAL00: 5th International Workshop on Information Retrieval with Asia Languages

September 30 - October 1, 2000

Hong Kong, China

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Adarsh Geoffrey Daniel KAlbert B(2023)Analyzing the likeness of a person based on DNS logs using machine learning2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)10.1109/IConSCEPT57958.2023.10170228(1-6)Online publication date: 25-May-2023
https://doi.org/10.1109/IConSCEPT57958.2023.10170228
Dutta JKim YDominic D(2023)Comparative Analysis of Various Ensemble Approaches for Web Page ClassificationData Engineering and Data Science10.1002/9781119841999.ch6(137-172)Online publication date: 5-Sep-2023
https://doi.org/10.1002/9781119841999.ch6
Echihabi KTsandilas TGogolou ABezerianos APalpanas T(2022)ProS: data series progressive k-NN similarity search and classification with probabilistic quality guaranteesThe VLDB Journal10.1007/s00778-022-00771-z32:4(763-789)Online publication date: 30-Nov-2022
https://doi.org/10.1007/s00778-022-00771-z
Lassri SBenlahmar ETragha A(2022)Web Page Classification Based on an Accurate Technique for Key Data ExtractionAdvanced Intelligent Systems for Sustainable Development (AI2SD’2020)10.1007/978-3-030-90639-9_91(1124-1131)Online publication date: 10-Feb-2022
https://doi.org/10.1007/978-3-030-90639-9_91
Sharma MSharma M(2021)LEVERAGING DATA MINING TECHNIQUES IN DEVELOPING AN INTEGRATED FRAMEWORK TO PREDICT THE HEALTH PREDICTIONSInternational Journal of Research in Medical Sciences & Technology10.37648/ijrmst.v11i02.00712:1Online publication date: 31-Dec-2021
https://doi.org/10.37648/ijrmst.v11i02.007
Gupta ABhatia R(2021)Ensemble approach for web page classificationMultimedia Tools and Applications10.1007/s11042-021-10891-3Online publication date: 15-Apr-2021
https://doi.org/10.1007/s11042-021-10891-3
Dutta JKim YDominic D(2020)Comparison of Gradient Boosting and Extreme Boosting Ensemble Methods for Webpage Classification2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)10.1109/ICRCICN50933.2020.9296176(77-82)Online publication date: 26-Nov-2020
https://doi.org/10.1109/ICRCICN50933.2020.9296176
Kovačević AMašetić ZKečo D(2020)Naive Website Categorization Based on Text CoverageAdvanced Technologies, Systems, and Applications V10.1007/978-3-030-54765-3_30(435-448)Online publication date: 5-Nov-2020
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ElAraby MAbuelenin SMoftah HRashad M(2019)A new architecture for improving focused crawling using deep neural networkJournal of Intelligent & Fuzzy Systems10.3233/JIFS-182683(1-13)Online publication date: 15-Jun-2019
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Safae LHabib BAbderrahim T(2018)A Review of Machine Learning Algorithms for Web Page Classification2018 IEEE 5th International Congress on Information Science and Technology (CiSt)10.1109/CIST.2018.8596420(220-226)Online publication date: Oct-2018
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