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Found 3 result(s)

CiteSeerX

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CiteSeerx is an evolving scientific literature digital library and search engine that focuses primarily on the literature in computer and information science. CiteSeerx aims to improve the dissemination of scientific literature and to provide improvements in functionality, usability, availability, cost, comprehensiveness, efficiency, and timeliness in the access of scientific and scholarly knowledge. Rather than creating just another digital library, CiteSeerx attempts to provide resources such as algorithms, data, metadata, services, techniques, and software that can be used to promote other digital libraries. CiteSeerx has developed new methods and algorithms to index PostScript and PDF research articles on the Web.

Google Code Project Hosting

Google Code

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The Google Code Archive contains the data found on the Google Code Project Hosting Service, which turned down in early 2016. This archive contains over 1.4 million projects, 1.5 million downloads, and 12.6 million issues. Google Project Hosting powers Project Hosting on Google Code and Eclipse Labs. Project Hosting on Google Code Eclipse Labs. It provides a fast, reliable, and easy open source hosting service with the following features: Instant project creation on any topic; Git, Mercurial and Subversion code hosting with 2 gigabyte of storage space and download hosting support with 2 gigabytes of storage space; Integrated source code browsing and code review tools to make it easy to view code, review contributions, and maintain a high quality code base; An issue tracker and project wiki that are simple, yet flexible and powerful, and can adapt to any development process; Starring and update streams that make it easy to keep track of projects and developers that you care about.

Scientific Data Repository

Data Repository. Interactive Analytics, Exploration & Visualization.

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A machine learning data repository with interactive visual analytic techniques. This project is the first to combine the notion of a data repository with real-time visual analytics for interactive data mining and exploratory analysis on the web. State-of-the-art statistical techniques are combined with real-time data visualization giving the ability for researchers to seamlessly find, explore, understand, and discover key insights in a large number of public donated data sets. This large comprehensive collection of data is useful for making significant research findings as well as benchmark data sets for a wide variety of applications and domains and includes relational, attributed, heterogeneous, streaming, spatial, and time series data as well as non-relational machine learning data. All data sets are easily downloaded into a standard consistent format. We also have built a multi-level interactive visual analytics engine that allows users to visualize and interactively explore the data in a free-flowing manner.