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Kosmas Karadimitriou

Researcher at Louisiana State University

Publications -  21
Citations -  846

Kosmas Karadimitriou is an academic researcher from Louisiana State University. The author has contributed to research in topics: Image compression & Web page. The author has an hindex of 12, co-authored 21 publications receiving 841 citations. Previous affiliations of Kosmas Karadimitriou include University of Texas MD Anderson Cancer Center.

Papers
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Patent

Computer method and apparatus for extracting data from web pages

TL;DR: In this article, a computer method and apparatus for extracting information from a Web page is described, which is formed of an extractor coupled to receive Web pages from a source. But the extractor uses natural language processing to extract desired information from the Web page.
Patent

Computer method and apparatus for collecting people and organization information from Web sites

TL;DR: In this article, a Web site of potential interest is accessed and a subset of web pages from the accessed site are determined for processing. But, according to types of contents found on a subject Web page, extraction of people and organization information is enabled.
Patent

Method for maintaining people and organization information

TL;DR: In this paper, the authors present a method that provides continual updates to the information stored in the database by the people named by the automated means and by the means of a link from the invention database to a third party data system.
Patent

Data mining system

TL;DR: In this paper, a computer automated method and system mines from a global computer network information about people and organizations, including automated crawling means, a distributor controlling the crawling means processing, an extractor storing extracted information of interest in a database, an integrator and post-processor.
Patent

Computer method and apparatus for determining content types of web pages

TL;DR: In this paper, a predefined set of potential content types of a subject Web page is first provided, and then a Bayesian network combines the test results to provide indications of the types of contents detected on the subject web page.