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YAGO2 - D5: Databases and Information Systems (Max-Planck-Institut für Informatik)

YAGO2 - D5: Databases and Information Systems (Max-Planck-Institut für Informatik)
Overview YAGO is a huge semantic knowledge base, derived from Wikipedia WordNet and GeoNames. Currently, YAGO has knowledge of more than 10 million entities (like persons, organizations, cities, etc.) and contains more than 120 million facts about these entities. YAGO is special in several ways: The accuracy of YAGO has been manually evaluated, proving a confirmed accuracy of 95%. Every relation is annotated with its confidence value.YAGO combines the clean taxonomy of WordNet with the richness of the Wikipedia category system, assigning the entities to more than 350,000 classes.YAGO is an ontology that is anchored in time and space. YAGO is developed jointly with the DBWeb group at Télécom ParisTech University.

http://www.mpi-inf.mpg.de/departments/databases-and-information-systems/research/yago-naga/yago/

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Mondrian (software) Mondrian is a general-purpose statistical data-visualization system. It features outstanding visualization techniques for data of almost any kind, and has its particular strength compared to other tools when working with Categorical Data, Geographical Data and LARGE Data. All plots in Mondrian are fully linked, and offer various interactions and queries. Any case selected in a plot in Mondrian is highlighted in all other plots. word2vec - Tool for computing continuous distributed representations of words. This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research. The word2vec tool takes a text corpus as input and produces the word vectors as output. It first constructs a vocabulary from the training text data and then learns vector representation of words. The resulting word vector file can be used as features in many natural language processing and machine learning applications. A simple way to investigate the learned representations is to find the closest words for a user-specified word.

Freebase Freebase is a large collaborative knowledge base consisting of metadata composed mainly by its community members. It is an online collection of structured data harvested from many sources, including individual 'wiki' contributions.[2] Freebase aims to create a global resource which allows people (and machines) to access common information more effectively. It was developed by the American software company Metaweb and has been running publicly since March 2007. Metaweb was acquired by Google in a private sale announced July 16, 2010.[3] Google's Knowledge Graph is powered in part by Freebase.[4] Freebase data is freely available for commercial and non-commercial use under a Creative Commons Attribution License, and an open API, RDF endpoint, and database dump are provided for programmers. Overview[edit]

Phenomenology First published Sun Nov 16, 2003; substantive revision Mon Dec 16, 2013 Phenomenology is the study of structures of consciousness as experienced from the first-person point of view. The central structure of an experience is its intentionality, its being directed toward something, as it is an experience of or about some object. YAGO-NAGA - D5: Databases and Information Systems (Max-Planck-Institut für Informatik) AIDA is a method, implemented in an online tool, for disambiguating mentions of named entities that occur in natural-language text or Web tables. AMIE (Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases) is a joint project with the Ontologies group. ANGIE is an active knowledge system for interactive exploration. claudio martella In the past, I’ve written about Google Pregel. At the time, as it was quite obvious, there was no implementation of anything like Pregel out there of any kind, not to mention Open Source. Now things have changed, so I’d like to give a quick list of the projects out there that might help you getting started with this technology, as I see that very often people ask what the difference is between all of them. I have direct experience only with the Java implementations, so I can talk about them a bit more extensively.

Semantic network Typical standardized semantic networks are expressed as semantic triples. History[edit] Example of a semantic network "Semantic Nets" were first invented for computers by Richard H. Richens of the Cambridge Language Research Unit in 1956 as an "interlingua" for machine translation of natural languages.[2] They were independently developed by Robert F. Catalog The Socrata Open Data API (SODA) allows software developers to access data hosted in Socrata data sites programmatically. Developers can create applications that use the SODA APIs to visualize and “mash-up” Socrata datasets in new and exciting ways. Create an iPhone application that visualizes government spending in your area, a web application that allows citizens to look up potential government benefits they'd overlooked, or a service that automatically emails you when new earmarks are added to bills that you wish to track. To start accessing this dataset programmatically, use the API endpoint provided below.

Phenomenology in psychology Assessment | Biopsychology | Comparative | Cognitive | Developmental | Language | Individual differences | Personality | Philosophy | Social |Methods | Statistics | Clinical | Educational | Industrial | Professional items | World psychology | Psychology:Debates · Journals · Psychologists Nevertheless, one abiding feature of 'experiences' is that, in principle, they are not directly observable by any external observer. The quality or nature of a given experience is often referred to by the term qualia, whose archetypical exemplar is "redness".

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