scholarly journals Web Crawler: Design And Implementation For Extracting Article-Like Contents

2020 ◽  
pp. 144-151
Author(s):  
Ngo Le Huy Hien ◽  
Thai Quang Tien ◽  
Nguyen Van Hieu

The World Wide Web is a large, wealthy, and accessible information system whose users are increasing rapidly nowadays. To retrieve information from the web as per users’ requests, search engines are built to access web pages. As search engine systems play a significant role in cybernetics, telecommunication, and physics, many efforts were made to enhance their capacity.However, most of the data contained on the web are unmanaged, making it impossible to access the entire network at once by current search engine system mechanisms. Web Crawler, therefore, is a critical part of search engines to navigate and download full texts of the web pages. Web crawlers may also be applied to detect missing links and for community detection in complex networks and cybernetic systems. However, template-based crawling techniques could not handle the layout diversity of objects from web pages. In this paper, a web crawler module was designed and implemented, attempted to extract article-like contents from 495 websites. It uses a machine learning approach with visual cues, trivial HTML, and text-based features to filter out clutters. The outcomes are promising for extracting article-like contents from websites, contributing to the search engine systems development and future research gears towards proposing higher performance systems.

2013 ◽  
Vol 303-306 ◽  
pp. 2311-2316
Author(s):  
Hong Shen Liu ◽  
Peng Fei Wang

The structures and contents of researching search engines are presented and the core technology is the analysis technology of web pages. The characteristic of analyzing web pages in one website is studied, relations between the web pages web crawler gained at two times are able to be obtained and the changed information among them are found easily. A new method of analyzing web pages in one website is introduced and the method analyzes web pages with the changed information of web pages. The result of applying the method shows that the new method is effective in the analysis of web pages.


A web crawler is also called spider. For the intention of web indexing it automatically searches on the WWW. As the W3 is increasing day by day, globally the number of web pages grown massively. To make the search sociable for users, searching engine are mandatory. So to discover the particular data from the WWW search engines are operated. It would be almost challenging for mankind devoid of search engines to find anything from the web unless and until he identifies a particular URL address. A central depository of HTML documents in indexed form is sustained by every search Engine. Every time an operator gives the inquiry, searching is done at the database of indexed web pages. The size of a database of every search engine depends on the existing page on the internet. So to increase the proficiency of search engines, it is permitted to store only the most relevant and significant pages in the database.


Author(s):  
GAURAV AGARWAL ◽  
SACHI GUPTA ◽  
SAURABH MUKHERJEE

Today, web servers, are the key repositories of the information & internet is the source of getting this information. There is a mammoth data on the Internet. It becomes a difficult job to search out the accordant data. Search Engine plays a vital role in searching the accordant data. A search engine follows these steps: Web crawling by crawler, Indexing by Indexer and Searching by Searcher. Web crawler retrieves information of the web pages by following every link on the site. Which is stored by web search engine then the content of the web page is indexed by the indexer. The main role of indexer is how data can be catch soon as per user requirements. As the client gives a query, Search Engine searches the results corresponding to this query to provide excellent output. Here ambition is to enroot an algorithm for search engine which may response most desirable result as per user requirement. In this a ranking method is used by the search engine to rank the web pages. Various ranking approaches are discussed in literature but in this paper, ranking algorithm is proposed which is based on parent-child relationship. Proposed ranking algorithm is based on priority assignment phase of Heterogeneous Earliest Finish Time (HEFT) Algorithm which is designed for multiprocessor task scheduling. Proposed algorithm works on three on range variable its means the density of keywords, number of successors to the nodes and the age of the web page. Density shows the occurrence of the keyword on the particular web page. Numbers of successors represent the outgoing link to a single web page. Age is the freshness value of the web page. The page which is modified recently is the freshest page and having the smallest age or largest freshness value. Proposed Technique requires that the priorities of each page to be set with the downward rank values & pages are arranged in ascending/ Descending order of their rank values. Experiments show that our algorithm is valuable. After the comparison with Google we find that our Algorithm is performing better. For 70% problems our algorithm is working better than Google.


Author(s):  
Anuradha T ◽  
Tayyaba Nousheen

The web is the heap and huge collection of wellspring of data. The Search Engine are used for retrieving the information from World Wide Web (WWW). Search Engines are helpful for searching user keywords and provide the accurate result in fraction of seconds. This paper proposed Machine Learning based search engine which will give more relevant user searches in the form of web pages. To display the user entered query search engine plays a major role of basic interface. Every site comprises of the heaps of site pages that are being made and sent on the server.


2019 ◽  
Vol 8 (S2) ◽  
pp. 35-38
Author(s):  
Mu. Annalakshmi ◽  
A. Padmapriya

Finding the required information in the vast area of web has been increasingly difficult in recent days since the web is overloaded with enormous content in the form of text, images, audio and video. Search engines help in this context to some extent but there are difficulties with them also. This paper proposes a framework in XML for the web pages in results of the search engines which helps in information filtering and search engine optimization.


Author(s):  
Vijay Kasi ◽  
Radhika Jain

In the context of the Internet, a search engine can be defined as a software program designed to help one access information, documents, and other content on the World Wide Web. The adoption and growth of the Internet in the last decade has been unprecedented. The World Wide Web has always been applauded for its simplicity and ease of use. This is evident looking at the extent of the knowledge one requires to build a Web page. The flexible nature of the Internet has enabled the rapid growth and adoption of it, making it hard to search for relevant information on the Web. The number of Web pages has been increasing at an astronomical pace, from around 2 million registered domains in 1995 to 233 million registered domains in 2004 (Consortium, 2004). The Internet, considered a distributed database of information, has the CRUD (create, retrieve, update, and delete) rule applied to it. While the Internet has been effective at creating, updating, and deleting content, it has considerably lacked in enabling the retrieval of relevant information. After all, there is no point in having a Web page that has little or no visibility on the Web. Since the 1990s when the first search program was released, we have come a long way in terms of searching for information. Although we are currently witnessing a tremendous growth in search engine technology, the growth of the Internet has overtaken it, leading to a state in which the existing search engine technology is falling short. When we apply the metrics of relevance, rigor, efficiency, and effectiveness to the search domain, it becomes very clear that we have progressed on the rigor and efficiency metrics by utilizing abundant computing power to produce faster searches with a lot of information. Rigor and efficiency are evident in the large number of indexed pages by the leading search engines (Barroso, Dean, & Holzle, 2003). However, more research needs to be done to address the relevance and effectiveness metrics. Users typically type in two to three keywords when searching, only to end up with a search result having thousands of Web pages! This has made it increasingly hard to effectively find any useful, relevant information. Search engines face a number of challenges today requiring them to perform rigorous searches with relevant results efficiently so that they are effective. These challenges include the following (“Search Engines,” 2004). 1. The Web is growing at a much faster rate than any present search engine technology can index. 2. Web pages are updated frequently, forcing search engines to revisit them periodically. 3. Dynamically generated Web sites may be slow or difficult to index, or may result in excessive results from a single Web site. 4. Many dynamically generated Web sites are not able to be indexed by search engines. 5. The commercial interests of a search engine can interfere with the order of relevant results the search engine shows. 6. Content that is behind a firewall or that is password protected is not accessible to search engines (such as those found in several digital libraries).1 7. Some Web sites have started using tricks such as spamdexing and cloaking to manipulate search engines to display them as the top results for a set of keywords. This can make the search results polluted, with more relevant links being pushed down in the result list. This is a result of the popularity of Web searches and the business potential search engines can generate today. 8. Search engines index all the content of the Web without any bounds on the sensitivity of information. This has raised a few security and privacy flags. With the above background and challenges in mind, we lay out the article as follows. In the next section, we begin with a discussion of search engine evolution. To facilitate the examination and discussion of the search engine development’s progress, we break down this discussion into the three generations of search engines. Figure 1 depicts this evolution pictorially and highlights the need for better search engine technologies. Next, we present a brief discussion on the contemporary state of search engine technology and various types of content searches available today. With this background, the next section documents various concerns about existing search engines setting the stage for better search engine technology. These concerns include information overload, relevance, representation, and categorization. Finally, we briefly address the research efforts under way to alleviate these concerns and then present our conclusion.


2014 ◽  
Vol 543-547 ◽  
pp. 2941-2944 ◽  
Author(s):  
Guo Chao Liang ◽  
Cai Feng Cao

The LED optical design focused web crawler is proposed based on Shark-Search and topical dictionary. Then the crawling strategy is implemented by extending the web crawler Heritrix. The experimental results show that the design scheme (Topic-First) and its web crawler LED-Crawler can effectively capture the LED optical design relevant web pages. And compared to general search engines, LED-Crawler can improve the accuracy.


2001 ◽  
Vol 1 (3) ◽  
pp. 28-31 ◽  
Author(s):  
Valerie Stevenson

Looking back to 1999, there were a number of search engines which performed equally well. I recommended defining the search strategy very carefully, using Boolean logic and field search techniques, and always running the search in more than one search engine. Numerous articles and Web columns comparing the performance of different search engines came to different conclusions on the ‘best’ search engines. Over the last year, however, all the speakers at conferences and seminars I have attended have recommended Google as their preferred tool for locating all kinds of information on the Web. I confess that I have now abandoned most of my carefully worked out search strategies and comparison tests, and use Google for most of my own Web searches.


2005 ◽  
Vol 10 (4) ◽  
pp. 517-541 ◽  
Author(s):  
Mike Thelwall

The Web has recently been used as a corpus for linguistic investigations, often with the help of a commercial search engine. We discuss some potential problems with collecting data from commercial search engine and with using the Web as a corpus. We outline an alternative strategy for data collection, using a personal Web crawler. As a case study, the university Web sites of three nations (Australia, New Zealand and the UK) were crawled. The most frequent words were broadly consistent with non-Web written English, but with some academic-related words amongst the top 50 most frequent. It was also evident that the university Web sites contained a significant amount of non-English text, and academic Web English seems to be more future-oriented than British National Corpus written English.


The Dark Web ◽  
2018 ◽  
pp. 359-374
Author(s):  
Dilip Kumar Sharma ◽  
A. K. Sharma

ICT plays a vital role in human development through information extraction and includes computer networks and telecommunication networks. One of the important modules of ICT is computer networks, which are the backbone of the World Wide Web (WWW). Search engines are computer programs that browse and extract information from the WWW in a systematic and automatic manner. This paper examines the three main components of search engines: Extractor, a web crawler which starts with a URL; Analyzer, an indexer that processes words on the web page and stores the resulting index in a database; and Interface Generator, a query handler that understands the need and preferences of the user. This paper concentrates on the information available on the surface web through general web pages and the hidden information behind the query interface, called deep web. This paper emphasizes the Extraction of relevant information to generate the preferred content for the user as the first result of his or her search query. This paper discusses the aspect of deep web with analysis of a few existing deep web search engines.


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