Keyword query based focused Web crawler

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.

2014

A Web crawler is a computer program that browses the World Wide Web in a methodical, automated manner or in an orderly fashion. Web crawling is an important method for collecting data on, and keeping up with, the rapidly expanding Internet. A vast number of web pages are continually being added every day, and information is constantly changing. This Paper is an overview of various types of Web Crawlers and the policies like selection, re-visit, politeness, parallelization involved in it. The behavioral pattern of the Web crawler based on these policies is also taken for the study. The evolution of these web crawler from Basic general purpose web crawler to the latest Adaptive web crawler is studied.

As there is profound web development, there has been expanded enthusiasm for methods that help productively find profound web interfaces. Because of accessibility of inexhaustible information on web, seeking has a noteworthy effect. Ongoing examines place accentuation on the pertinence and strength of the information found, as the found examples closeness is a long way from the investigated. Notwithstanding their importance pages for any inquiry subject, the outcomes are colossal to be investigated. One issue of pursuit on the Web is that internet searchers return huge hit records with low accuracy. Clients need to filter applicable reports from insignificant ones by physically bringing and skimming pages. Another debilitating viewpoint is that URLs or entire pages are returned as list items. It is likely that the response to a client question is just part of the page. Recovering the entire page really leaves the errand of inquiry inside a page to Web clients. With these two viewpoints staying unaltered, Web clients won't be liberated from the substantial weight of perusing pages and finding required data, and data got from one pursuit will be characteristically constrained.

2021

Websites are getting richer and richer with information in different formats. The data that such sites possess today goes through millions of terabytes of data, but not every information that is on the net is useful. To enable the most efficient internet browsing for the user, one methodology is to use web crawler. This study presents web crawler methodology, the first steps of development, how it works, the different types of web crawlers, the benefits of using and comparing their operating methods which are the advantages and disadvantages of each algorithm used by them.

This Paper presents a study of web crawlers used in search engines. Nowadays finding meaningful information among the billions of information resources on the World Wide Web is a difficult task due to growing popularity of the Internet. This paper basically focuses on study of the various kinds of web crawler for finding the relevant information from World Wide Web. A web crawler is defined as an automated program that methodically scans through Internet pages and downloads any page that can be reached via links. A performance analysis of performance of intelligent crawler is presented and data mining algorithms are compared on the basis of crawlers usability.

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.

The web today contains a lot of information and it keeps on increasing everyday. Thus, due to the availability of abundant data on web, searching for some particular data in this collection has become very difficult. Emphasis is given to the relevance and robustness of data by the on-going researches. Although only relevant pages are to be considered for any search query but still huge data needs to be explored. Another important thing to keep in mind is that usually one's need may not be desirable for others. Crawling algorithms are thus crucial in selecting the pages that satisfy the user's need. This paper reviews the researches on web crawling algorithms used for searching.

Proceedings of National Conference on Recent Trends in Parallel Computing (RTPC - 2014)

There are billions of pages on World Wide Web where each page is denoted by URLs. Finding relevant information from these URLs is not easy. The information to be sought has to be found quickly, efficiently and very relevant. A web crawler is used to find what information each URLs contain. Web crawler traverses the World Wide Web in systematic manner, downloads the page and sends the information over to search engine so that it get indexed. There are various types of web crawlers and each provides some improvement over the other. This paper presents an overview of web crawler, its architecture and identifies types of crawlers with their architecture, namely incremental, parallel, distributed, focused and hidden web crawler.

2013

A key issue in designing a focused Web crawler is how to determine whether an unvisited URL is relevant to the search topic. Effective relevance prediction can help avoid downloading and visiting many irrelevant pages. In this module, we propose a new learning-based approach to improve relevance prediction in focused Web crawlers. For this study, we chose Naïve Bayesian as the base prediction model, which however can be easily switched to a different prediction model. The performance of a focused crawler depends mostly on the richness of links in the specific topic being searched, and focused crawling usually relies on a general web search engine for providing starting points. Key Terms: URL; focused crawler; classifier; relevance prediction; links; search engine; ranking

2011

The World Wide Web (WWW) has grown from a few thousand pages in 1993 to more than eight billion pages at present. Due to this explosion in size, web search engines are becoming increasingly important as the primary means of locating relevant information. This research aims to build a crawler that crawls the most important web pages, a crawling system has been built which consists of three main techniques. The first is Best-First Technique which is used to select the most important page. The second is Distributed Crawling Technique which based on UbiCrawler. It is used to distribute the URLs of the selected web pages to several machines. And the third is Duplicated Pages Detecting Technique by using a proposed document fingerprint algorithm.