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Computing semantic relatedness using Wikipedia-based explicit semantic analysis

by Evgeniy Gabrilovich, Shaul Markovitch - In Proceedings of the 20th International Joint Conference on Artificial Intelligence , 2007
"... Computing semantic relatedness of natural language texts requires access to vast amounts of common-sense and domain-specific world knowledge. We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from Wikipedi ..."
Abstract - Cited by 562 (9 self) - Add to MetaCart
Computing semantic relatedness of natural language texts requires access to vast amounts of common-sense and domain-specific world knowledge. We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from

MapReduce: Simplified data processing on large clusters.

by Jeffrey Dean , Sanjay Ghemawat - In Proceedings of the Sixth Symposium on Operating System Design and Implementation (OSDI-04), , 2004
"... Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details of ..."
Abstract - Cited by 3439 (3 self) - Add to MetaCart
Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines. The run-time system takes care of the details

From Data Mining to Knowledge Discovery in Databases.

by Usama Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth - AI Magazine, , 1996
"... ■ Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. What is all the excitement about? This article provides an overview of this emerging field, clarifying how data mining and knowledge discovery in database ..."
Abstract - Cited by 538 (0 self) - Add to MetaCart
research directions in the field. A cross a wide variety of fields, data are being collected and accumulated at a dramatic pace. There is an urgent need for a new generation of computational theories and tools to assist humans in extracting useful information (knowledge) from the rapidly growing volumes

Large scale multiple kernel learning

by Sören Sonnenburg, Gunnar Rätsch , Christin Schäfer, Bernhard Schölkopf - JOURNAL OF MACHINE LEARNING RESEARCH , 2006
"... While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic combinations of kernel matrices for classification, leading to a convex quadratically constrained quadratic program. We s ..."
Abstract - Cited by 340 (20 self) - Add to MetaCart
show that the proposed algorithm works for hundred thousands of examples or hundreds of kernels to be combined, and helps for automatic model selection, improving the interpretability of the learning result. In a second part we discuss general speed up mechanism for SVMs, especially when used

A model for learning the semantics of pictures

by V. Lavrenko, R. Manmatha, J. Jeon - in NIPS , 2003
"... We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do this using a formalism that models the generation of annotated images. We assume that every image is divided into regions, e ..."
Abstract - Cited by 241 (9 self) - Add to MetaCart
We propose an approach to learning the semantics of images which allows us to automatically annotate an image with keywords and to retrieve images based on text queries. We do this using a formalism that models the generation of annotated images. We assume that every image is divided into regions

DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language

by Yuan Yu, Michael Isard, Dennis Fetterly, Mihai Budiu, Úlfar Erlingsson, Pradeep Kumar, Gunda Jon Currey
"... DryadLINQ is a system and a set of language extensions that enable a new programming model for large scale distributed computing. It generalizes previous execution environments such as SQL, MapReduce, and Dryad in two ways: by adopting an expressive data model of strongly typed.NET objects; and by s ..."
Abstract - Cited by 273 (27 self) - Add to MetaCart
made up of thousands of computers, ensures efficient, reliable execution of this plan. We describe the implementation of the DryadLINQ compiler and runtime. We evaluate DryadLINQ on a varied set of programs drawn from domains such as web-graph analysis, large-scale log mining, and machine learning. We

Voice puppetry

by Matthew Brand , 1999
"... Frames from a voice-driven animation, computed from a single baby picture and an adult model of facial control. Note the changes in upper facial expression. See figures 5, 6 and 7 for more examples of predicted mouth shapes. We introduce a method for predicting a control signal from another related ..."
Abstract - Cited by 298 (0 self) - Add to MetaCart
signal, and apply it to voice puppetry: Generating full facial animation from expressive information in an audio track. The voice puppet learns a facial control model from computer vision of real facial behavior, automatically incorporating vocal and facial dynamics such as co-articulation. Animation

Automatized Generating of GUIs for Domain-Specific Languages

by Michaela Bačíková, Milan Nosá ˇ L
"... Abstract. Domain-specific languages (DSLs) promise many advantages over general purpose languages (GPLs) and their usage is on the rise. That is one of the reasons for us at our university to teach the subject called Modelling and Generating of Software Architectures (MaGSA), where the students lear ..."
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Abstract. Domain-specific languages (DSLs) promise many advantages over general purpose languages (GPLs) and their usage is on the rise. That is one of the reasons for us at our university to teach the subject called Modelling and Generating of Software Architectures (MaGSA), where the students

Learning Hidden Markov Model Structure for Information Extraction

by Kristie Seymore, Andrew $i Mccallum, Ronald Rosenfeld T - in Proc. AAAI’99 Workshop Machine Learning for Information Extraction , 1999
"... Statistical machine learning techniques, while well proven in fields such as speech recognition, are just beginning to be applied to the information extraction domain. We explore the use of hidden Markov models for information extraction tasks, specifically focusing on how to learn model structure f ..."
Abstract - Cited by 201 (10 self) - Add to MetaCart
Statistical machine learning techniques, while well proven in fields such as speech recognition, are just beginning to be applied to the information extraction domain. We explore the use of hidden Markov models for information extraction tasks, specifically focusing on how to learn model structure

MBT: A Memory-Based Part of Speech Tagger-Generator

by Walter Daelemans , Jakub Zavrel, Peter Berck, Steven Gillis - PROC. OF FOURTH WORKSHOP ON VERY LARGE CORPORA , 1996
"... We introduce a memory-based approach to part of speech tagging. Memory-based learning is a form of supervised learning based on similarity-based reasoning. The part of speech tag of a word in a particular context is extrapolated from the most similar cases held in memory. Supervised learning approac ..."
Abstract - Cited by 236 (56 self) - Add to MetaCart
approaches are useful when a tagged corpus is available as an example of the desired output of the tagger. Based on such a corpus, the tagger-generator automatically builds a tagger which is able to tag new text the same way, diminishing development time for the construction of a tagger considerably. Memory
Results 1 - 10 of 2,060