A Fuzzy Logic based Solution for Network Traffic Problems in Migrating Parallel Crawlers (original) (raw)
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SMART WEB CRAWLING WITH FUZZY CLUSTERING
Since its launch, Internet has become a vast source of information in Natural Language. Accessing such information corpus efficiently is a matter of discussion and research in various fields. Search engines are in charge of grouping and classifying web pages in terms of keywords. Web Crawler processes perform such tasks. During exploration the websites are indexed according to different metrics, feeding the knowledge base of the search engine. Exploring hypertext and its links presents an exponential order of growth in terms of computational time. This paper presents the GDARIM project a Web Crawler that presents techniques that improve the accuracy of the information retrieved on a crawling process for a given set of keywords. GDARIM implements an exploration method based on Fuzzy Clustering, which takes into consideration the semantic distance of terms transposing knowledge into a multidimensional space. GDARIM is also the data source input for an Opinion Mining system that needs preprocessed information from preselected sources.
A Methodical Study of Web Crawler
World Wide Web (or simply web) is a massive, wealthy, preferable, effortlessly available and appropriate source of information and its users are increasing very swiftly now a day. To salvage information from web, search engines are used which access web pages as per the requirement of the users. The size of the web is very wide and contains structured, semi structured and unstructured data. Most of the data present in the web is unmanaged so it is not possible to access the whole web at once in a single attempt, so search engine use web crawler. Web crawler is a vital part of the search engine. It is a program that navigates the web and downloads the references of the web pages. Search engine runs several instances of the crawlers on wide spread servers to get diversified information from them. The web crawler crawls from one page to another in the World Wide Web, fetch the webpage, load the content of the page to search engine's database and index it. Index is a huge database of words and text that occur on different webpage. This paper presents a systematic study of the web crawler. The study of web crawler is very important because properly designed web crawlers always yield well results most of the time.
International Journal on Web Service Computing, 2012
The size of the internet is large and it had grown enormously search engines are the tools for Web site navigation and search. Search engines maintain indices for web documents and provide search facilities by continuously downloading Web pages for processing. This process of downloading web pages is known as web crawling. In this paper we propose the architecture for Effective Migrating Parallel Web Crawling approach with domain specific and incremental crawling strategy that makes web crawling system more effective and efficient. The major advantages of migrating parallel web crawler are that the analysis portion of the crawling process is done locally at the residence of data rather than inside the Web search engine repository. This significantly reduces network load and traffic which in turn improves the performance, effectiveness and efficiency of the crawling process. The another advantage of migrating parallel crawler is that as the size of the Web grows, it becomes necessary to parallelize a crawling process, in order to finish downloading web pages in a comparatively shorter time. Domain specific crawling will yield high quality pages. The crawling process will migrate to host or server with specific domain and start downloading pages within specific domain. Incremental crawling will keep the pages in local database fresh thus increasing the quality of downloaded pages.
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The Issues and Challenges with the Web Crawlers
A search engine is an information retrieval system designed to minimize the time required to find information over the Web of hyperlinked documents. It provides a user interface that enables the users to specify criteria about an item of interest and searches the same from locally maintained databases. The criteria are referred to as a search query. The search engine is a cascade model comprising of crawling, indexing, and searching modules. Crawling is the first stage that downloads Web documents, which are indexed by the indexer for later use by searching module, with a feedback from other stages. This module could also provide on-demand crawling services for search engines, if required. This paper discusses the issues and challenges involved in the design of the various types of crawlers.
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Making use of search engines is most popular Internet task apart from email. Currently, all major search engines employ web crawlers because effective web crawling is a key to the success of modern search engines. Web crawlers can give vast amounts of web information possible to explore the web entirely by humans. Therefore, crawling algorithms are crucial in selecting the pages that satisfy the users’ needs. Crawling cultural and/or linguistic specific resources from the borderless Web raises many challenging issues. This paper will review various web crawlers used for searching the web while also exploring the use of various algorithms to retrieve web pages. Keyword: Web Search Engine, Web Crawlers, Web Crawling Algorithms.
Agent-Based Approach for Web Crawling
Since its creation in 1990, World Wide Web has increased the popularity of Internet which becomes an important source of information or services for all people over the world. The dynamic nature of the Web draws attention to the need for continuous support and updating of Web information retrieval systems. Web crawling is the process of discovery and maintenance of large-scale web data. Crawlers achieve this process by following the Web pages hyperlinks to automatically download a partial snapshot of the Web. In this paper, an agent-based approach, through three scenarios, for parallel and distributed Web crawling is presented. Simulations with ns2 show that the cloning based mobile agents scenario outperforms the single and multiple mobile agents scenarios.