A <i>web crawler</i> is a program that "walks" the Web to gather web resources. In order to scale to the ever-increasing Web, multiple crawling agents may be deployed in a distributed fashion to retrieve web data co-operatively. A common approach is to divide the Web into many partitions with an agent assigned to crawl within each one. If an agent obtains a web resource that is not from its partition, the resource will be transferred to the rightful owner. This thesis proposes a novel approach to distributed web data gathering by partitioning the Web into topics. The proposed approach employs multiple focused crawlers to retrieve pages from various topics. When a crawler retrieves a page of another topic, it transfers the page to the appropriate crawler. This approach is known as <i>topic-oriented collaborative web crawling</i>. An implementation of the system was built and experimentally evaluated. In order to identify the topic of a web page, a topic classifier was incorporated into the crawling system. As the classifier categorizes only English pages, a language identifier was also introduced to distinguish English pages from non-English ones. From the experimental results, we found that redundance retrieval was low and that a resource, retrieved by an agent, is six times more likely to be retained than a system that uses conventional hashing approach. These numbers were viewed as strong indications that <i>topic-oriented collaborative web crawling system</i> is a viable approach to web data gathering.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/1040 |
Date | January 2001 |
Creators | Chung, Chiasen |
Publisher | University of Waterloo |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
Format | application/pdf, 733407 bytes, application/pdf |
Rights | Copyright: 2001, Chung, Chiasen. All rights reserved. |
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