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Format Identification for Digital Objects (FIDO) - Open Preservation Foundation Format Identification for Digital Objects (fido). FIDO is a command-line tool to identify the file formats of digital objects. It is designed for simple integration into automated work-flows. License information FIDO is distributed under the Apache 2 license. Wikipedia:Researching with Wikipedia - Wikipedia For a quick and simple guide to using Wikipedia in Research, see WP:Research help. Wikipedia can be a great tool for learning and researching information. However, as with all reference works, not everything in Wikipedia is accurate, comprehensive, or unbiased. Many of the general rules of thumb for conducting research apply to Wikipedia, including:

List of datasets for machine learning research - Wikipedia These datasets are used for machine learning research and have been cited in peer-reviewed academic journals and other publications. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets.[1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce.[2][3][4][5] This list aggregates high-quality datasets that have been shown to be of value to the machine learning research community from multiple different data repositories to provide greater coverage of the topic than is otherwise available.

Upper ontology - Wikipedia A number of upper ontologies have been proposed, each with its own proponents. Each upper ontology can be considered as a computational implementation of natural philosophy, which itself is a more empirical method for investigating the topics within the philosophical discipline of physical ontology. Library classification systems predate upper ontology systems. Public Domain Collections: Free to Share & Reuse That means everyone has the freedom to enjoy and reuse these materials in almost limitless ways. The Library now makes it possible to download such items in the highest resolution available directly from the Digital Collections website. Search Digital Collections No permission required. datasets The DBpedia data set uses a large multi-domain ontology which has been derived from Wikipedia as well as localized versions of DBpedia in more than 100 languages. 1 Background Wikipedia has grown into one of the central knowledge sources of mankind and is maintained by thousands of contributors.

The Sweet Compendium of Ontology Building Tools Download as PDF Well, for another client and another purpose, I was goaded into screening my Sweet Tools listing of semantic Web and -related tools and to assemble stuff from every other nook and cranny I could find. The net result is this enclosed listing of some 140 or so tools — most open source — related to semantic Web ontology building in one way or another. Ever since I wrote my Intrepid Guide to Ontologies nearly three years ago (and one of the more popular articles of this site, though it is now perhaps a bit long in the tooth), I have been intrigued with how these semantic structures are built and maintained.

Carrot2 Clustering Engine Carrot2 Search Results Clustering Engine Carrot2 organizes your search results into topics. With an instant overview of what's available, you will quickly find what you're looking for. Attention Ecology: Trend Circulation and the Virality Threshold Abstract This article demonstrates the use of data mining methodologies for the study and research of social media in the digital humanities. Drawing from recent convergences in writing, rhetoric, and DH research, this article investigates how trends operate within complex networks. Through a study of trend data mined from Twitter, this article suggests the possibility of identifying a virality threshold for Twitter trends, and the possibility that such a threshold has broader implications for attention ecology research in the digital humanities.

Iris is an AI to help science R&D Most startups have a pitch. The team behind Iris AI has two: right now they’ve created an AI-powered science assistant that functions like a search tool, helping researchers track down relevant journal papers without having to know the right keywords for their search. But in future their big vision is their artificially intelligent baby grows up to become a scientist in her own right — capable of forming and even testing hypotheses, based on everything it’s going to learn in its science research assistant ‘first job’ role. Such is the multi-stage, big picture promise of artificial intelligence. Yet convincing customers to buy into AI’s potential now, at what is still a pretty nascent stage in the tech’s development, remains a challenge.

Oracle Buys Apiary, a Specialist in Application Programming Interfaces Oracle says it is buying Apiary, a company that specializes in managing and monitoring application programming interfaces, or APIs, which offer standard ways to connect software applications. Both software giants and large Fortune 500 companies are scrambling to add expertise in building, monitoring, and documenting these crucial pieces of technology. Terms of the deal were not disclosed, but in a statement, Oracle (orcl, +1.68%) said Apiary, based in Prague and San Francisco, has: