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Topic

Hyperlink

About: Hyperlink is a(n) research topic. Over the lifetime, 4255 publication(s) have been published within this topic receiving 143894 citation(s). The topic is also known as: link.

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Journal ArticleDOI
Sergey Brin1, Lawrence Page1Institutions (1)
01 Apr 1998-
TL;DR: This paper provides an in-depth description of Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext and looks at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.

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Abstract: In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.

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14,045 citations


Journal Article
01 Jan 1998-Computer Networks
Abstract: In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want.

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13,327 citations


Journal ArticleDOI
09 Sep 1999-Nature
TL;DR: The World-Wide Web becomes a large directed graph whose vertices are documents and whose edges are links that point from one document to another, which determines the web's connectivity and consequently how effectively the authors can locate information on it.

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Abstract: Despite its increasing role in communication, the World-Wide Web remains uncontrolled: any individual or institution can create a website with any number of documents and links. This unregulated growth leads to a huge and complex web, which becomes a large directed graph whose vertices are documents and whose edges are links (URLs) that point from one document to another. The topology of this graph determines the web's connectivity and consequently how effectively we can locate information on it. But its enormous size (estimated to be at least 8×108 documents1) and the continual changing of documents and links make it impossible to catalogue all the vertices and edges.

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3,988 citations


Journal ArticleDOI
01 Sep 1987-IEEE Computer
TL;DR: A survey of existing hypertext systems, their applications, and their design is both an introduction to the world of hypertext and a survey of some of the most important design issues that go into fashioning a hypertext environment.

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Abstract: This article is a survey of existing hypertext systems, their applications, and their design. It is both an introduction to the world of hypertext and, at a deeper cut, a survey of some of the most important design issues that go into fashioning a hypertext environment. The concept of hypertext is quite simple: Windows on the screen are associated with objects in a database, and links are provided between these objects, both graphically (as labelled tokens) and in the database (as pointers). But this simple idea is creating much excitement. Several universities have created laboratories for research on hypertext, many articles have been written about the concept just within the last year, and the Smithsonian Institute has created a demonstration laboratory to develop and display hypertext technologies.

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2,537 citations


Journal ArticleDOI
Prithviraj Sen1, Galileo Namata1, Mustafa Bilgic1, Lise Getoor1  +2 moreInstitutions (1)
06 Sep 2008-Ai Magazine
TL;DR: This article introduces four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real-world data.

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Abstract: Many real-world applications produce networked data such as the world-wide web (hypertext documents connected via hyperlinks), social networks (for example, people connected by friendship links), communication networks (computers connected via communication links) and biological networks (for example, protein interaction networks). A recent focus in machine learning research has been to extend traditional machine learning classification techniques to classify nodes in such networks. In this article, we provide a brief introduction to this area of research and how it has progressed during the past decade. We introduce four of the most widely used inference algorithms for classifying networked data and empirically compare them on both synthetic and real-world data.

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1,910 citations


Network Information
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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20222
202158
202088
201982
2018106
2017133

Top Attributes

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Topic's top 5 most impactful authors

Mike Thelwall

35 papers, 1.8K citations

Han Woo Park

13 papers, 670 citations

Katsumi Tanaka

10 papers, 107 citations

Liwen Vaughan

10 papers, 491 citations

Soumen Chakrabarti

7 papers, 3.5K citations