About: URL redirection is a research topic. Over the lifetime, 418 publications have been published within this topic receiving 9583 citations. The topic is also known as: URL forwarding & redirection.
TL;DR: DAVID, the database for annotation, visualization and integrated discovery (DAVID), is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins.
Abstract: Summary: The database for annotation, visualization and integrated discovery (DAVID), which can be freely accessed at http://david.abcc.ncifcrf.gov/, is a web-based online bioinformatics resource that aims to provide tools for the functional interpretation of large lists of genes/proteins. It has been used by researchers from more than 5000 institutes worldwide, with a daily submission rate of ~1200 gene lists from ~400 unique researchers, and has been cited by more than 6000 scientific publications. However, the current web interface does not support programmatic access to DAVID, and the uniform resource locator (URL)-based application programming interface (API) has a limit on URL size and is stateless in nature as it uses URL request and response messages to communicate with the server, without keeping any state-related details. DAVID-WS (web service) has been developed to automate user tasks by providing stateful web services to access DAVID programmatically without the need for human interactions.
Availability: The web service and sample clients (written in Java, Perl, Python and Matlab) are made freely available under the DAVID License at http://david.abcc.ncifcrf.gov/content.jsp?file=WS.html.
Contact:xiaoli.jiao@nih.gov; rlempicki@nih.gov
TL;DR: In this article, a method and apparatus for tracking the navigation path of a user that has been directed to a second site on the WWW from a first sites on the Web is presented.
Abstract: A method and apparatus for tracking the navigation path of a user that has been directed to a second site on the WWW from a first site on the WWW. A URL is received at the second WWW site when the user is directed from the first site to the second site. At the second WWW site, information representative of an identity of the first WWW site is captured by identifying a first code in the URL. A destination web page is determined for the user, and a revised destination web page is formed by attaching a second code representative of the identity of the first WWW site into at least one selected web page link associated with the destination web page. The revised destination web page is then transmitted to the user.
TL;DR: In this paper, a method and system for sending and receiving Uniform Resource Locators (URLs) in electronic mail over the Internet is presented, where the user can click on the URL to look up the information corresponding to the URL.
Abstract: A method and system for sending and receiving Uniform Resource Locators (URLs) in electronic mail over the Internet. An electronic mail document containing a URL may have several different types. If the message type indicates a URL, when the received URL type document is read or browsed using a multimedia Internet browser, the URL is looked up so that the information corresponding to the URL is displayed without necessarily displaying any portion of the received message. If the received document is of the Hypertext Markup Language (HTML) type, the document may be displayed and a user may "click" on the URL to look up the information corresponding to the URL. If the received document is of the text type, the text may be converted to the HTML format and the HTML format document displayed so that a user may "click" on the URL in order to look up the information corresponding to the URL without the need to type in the URL address.
TL;DR: Fuzzy URL detection as mentioned in this paper automatically performs a fuzzy search that returns a list of URLs that most closely match what was originally entered into the browser address field, and the user can then select the correct URL from the list and launch the browser to the desired site, or to a directory or file within that site.
Abstract: A Web browser running on a client machine typically includes an address field in which a Uniform Resource Locator (URL) may be entered. The URL identifies a particular server (or file) located at a target Web site. If a given URL is entered incorrectly at the Web client, a fuzzy URL detection scheme automatically performs a fuzzy search that returns a list of URLs that most closely match what was originally entered into the browser address field. The user can then select the correct URL from the list and launch the browser to the desired site, or to a directory or file within that site. If the fuzzy search does not reveal a match, the browser may contact a server dedicated to performing a broader fuzzy search. In another alternative, the browser contacts a Web server and the fuzzy search is implemented at the Web server in order to return a particular file.
TL;DR: This paper develops methods to discover correlated URL redirect chains using the frequently shared URLs and to determine their suspiciousness, and presents WarningBird as a near real-time system for classifying suspicious URLs in the Twitter stream.
Abstract: Twitter is prone to malicious tweets containing URLs for spam, phishing, and malware distribution. Conventional Twitter spam detection schemes utilize account features such as the ratio of tweets containing URLs and the account creation date, or relation features in the Twitter graph. These detection schemes are ineffective against feature fabrications or consume much time and resources. Conventional suspicious URL detection schemes utilize several features including lexical features of URLs, URL redirection, HTML content, and dynamic behavior. However, evading techniques such as time-based evasion and crawler evasion exist. In this paper, we propose WarningBird, a suspicious URL detection system for Twitter. Our system investigates correlations of URL redirect chains extracted from several tweets. Because attackers have limited resources and usually reuse them, their URL redirect chains frequently share the same URLs. We develop methods to discover correlated URL redirect chains using the frequently shared URLs and to determine their suspiciousness. We collect numerous tweets from the Twitter public timeline and build a statistical classifier using them. Evaluation results show that our classifier accurately and efficiently detects suspicious URLs. We also present WarningBird as a near real-time system for classifying suspicious URLs in the Twitter stream.