Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/31688
Title: An architecture for SCS: A specialized web crawler on the topic of security
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
Özmutlu, Hüseyin Cenk
Özmutlu, Seda
ABH-5209-2020
AAH-4480-2021
6603061328
6603660605
Keywords: Computer science
Information science and library science
Web crawler
Focused crawling
Specialized crawling
Artificial intelligence
Artificial neural networks
Rule-based systems
Security
World-wide-web
Search engines
Information
Issue Date: 2004
Publisher: Information Today
Citation: Özmutlu, H.C. ve Özmutlu, S. (2004). “An architecture for SCS: A specialized web crawler on the topic of security”. ASIST 2004: Proceedings of the 67. Asist Annual Meeting, Proceedings of the ASIST Annual Meeting, 41, 317-326.
Abstract: Mining for correct and relevant information in the World Wide Web is a difficult task, handled by Web crawlers. This study outlines the components of a specialized crawler on the topic of security (SCS) that heavily makes use of artificial neural networks and rule-based expert systems to establish successful focused crawling on the topic of security. SCS is designed to find, index and follow the updates of Web pages of interest, and proposes new approaches for reaching relevant pages, which might stay hidden to other crawling approaches. SCS consists of four new page explorers, a database of relevant pages, a relevance evaluator using artificial neural networks and an updater using rule-based expert systems. SCS is a multi-threaded multi-object Java Applet and Application combination with embedded SOL and PHP elements and is applicable on single or multiple machines through parallel processing with its expandable and modular structure.
Description: Bu çalışma, 12-17 Kasım 2004 tarihleri arasında Rhode Island[Amerika Birleşik Devletleri]’de düzenlenen 67. Asist Annual Meeting'de bildiri olarak sunulmuştur.
URI: https://doi.org/10.1002/meet.1450410138
https://asistdl.onlinelibrary.wiley.com/doi/full/10.1002/meet.1450410138
http://hdl.handle.net/11452/31688
ISSN: 0044-7870
Appears in Collections:Scopus
Web of Science

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