Results 1 - 10 of 14,571

The Tradeoffs Between Open and Traditional Relation Extraction

by Michele Banko, Oren Etzioni
"... Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tailored to massive and heterogeneous corpora such as the Web. An Open IE system extracts a diverse set of relational tuples ..."
Abstract - Cited by 112 (10 self) - Add to MetaCart
that it achieves increased precision and nearly double the recall than the model employed by TEXTRUNNER, the previous stateof-the-art Open IE system. Second, when the number of target relations is small, and their names are known in advance, we show that O-CRF is able to match the precision of a traditional

Image retrieval: Current techniques, promising directions and open issues

by Yong Rui, Thomas S. Huang - Journal of Visual Communication and Image Representation , 1999
"... This paper provides a comprehensive survey of the technical achievements in the research area of image retrieval, especially content-based image retrieval, an area that has been so active and prosperous in the past few years. The survey includes 100+ papers covering the research aspects of image fea ..."
Abstract - Cited by 507 (15 self) - Add to MetaCart
feature representation and extraction, multidimensional indexing, and system design, three of the fundamental bases of content-based image retrieval. Furthermore, based on the state-of-the-art technology available now and the demand from real-world applications, open research issues are identified

A Bayesian method for the induction of probabilistic networks from data

by Gregory F. Cooper, EDWARD HERSKOVITS - MACHINE LEARNING , 1992
"... This paper presents a Bayesian method for constructing probabilistic networks from databases. In particular, we focus on constructing Bayesian belief networks. Potential applications include computer-assisted hypothesis testing, automated scientific discovery, and automated construction of probabili ..."
Abstract - Cited by 1400 (31 self) - Add to MetaCart
network from a database of cases. Finally, we relate the methods in this paper to previous work, and we discuss open problems.

Predicting Internet Network Distance with Coordinates-Based Approaches

by T. S. Eugene Ng, Hui Zhang - In INFOCOM , 2001
"... In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which is bas ..."
Abstract - Cited by 631 (6 self) - Add to MetaCart
In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which

The use of MMR, diversity-based reranking for reordering documents and producing summaries

by Jaime Carbonell, Jade Goldstein - In SIGIR , 1998
"... jadeQcs.cmu.edu Abstract This paper presents a method for combining query-relevance with information-novelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR) criterion strives to reduce redundancy while maintaining query relevance in re-ranking retrieved docum ..."
Abstract - Cited by 768 (14 self) - Add to MetaCart
“marginal relevance ”- i.e. a document has high marginal relevance if it is both relevant to the query and contains minimal similarity to previously selected documents. We strive to maximize-marginal relevance in retrieval and summarization, hence we label our method “maximal marginal relevanci ” (MMR).

Loopy belief propagation for approximate inference: An empirical study. In:

by Kevin P Murphy , Yair Weiss , Michael I Jordan - Proceedings of Uncertainty in AI, , 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon-limit performanc ..."
Abstract - Cited by 676 (15 self) - Add to MetaCart
Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon

MonoSLAM: Realtime single camera SLAM

by Andrew J. Davison, Ian D. Reid, Nicholas D. Molton, Olivier Stasse - IEEE Transactions on Pattern Analysis and Machine Intelligence , 2007
"... Abstract—We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the “pure vision ” domain of ..."
Abstract - Cited by 490 (26 self) - Add to MetaCart
Abstract—We present a real-time algorithm which can recover the 3D trajectory of a monocular camera, moving rapidly through a previously unknown scene. Our system, which we dub MonoSLAM, is the first successful application of the SLAM methodology from mobile robotics to the “pure vision ” domain

Open information extraction from the web

by Michele Banko, Michael J Cafarella, Stephen Soderland, Matt Broadhead, Oren Etzioni - IN IJCAI , 2007
"... Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, pre-specified requests from small homogeneous corpora (e.g., extract the location and time of seminars from a set of announcements). Shifting to a new domain requires the user to name the target relations and to ma ..."
Abstract - Cited by 373 (39 self) - Add to MetaCart
page corpus that compare TEXTRUNNER with KNOWITALL, a state-of-the-art Web IE system. TEXTRUNNER achieves an error reduction of 33% on a comparable set of extractions. Furthermore, in the amount of time it takes KNOWITALL to perform extraction for a handful of pre-specified relations, TEXTRUNNER

Learning Information Extraction Rules for Semi-structured and Free Text

by Stephen Soderland, Claire Cardie, Raymond Mooney - Machine Learning , 1999
"... . A wealth of on-line text information can be made available to automatic processing by information extraction (IE) systems. Each IE application needs a separate set of rules tuned to the domain and writing style. WHISK helps to overcome this knowledge-engineering bottleneck by learning text extract ..."
Abstract - Cited by 437 (10 self) - Add to MetaCart
. A wealth of on-line text information can be made available to automatic processing by information extraction (IE) systems. Each IE application needs a separate set of rules tuned to the domain and writing style. WHISK helps to overcome this knowledge-engineering bottleneck by learning text

From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images

by Alfred M. Bruckstein, David L. Donoho, Michael Elad , 2007
"... A full-rank matrix A ∈ IR n×m with n < m generates an underdetermined system of linear equations Ax = b having infinitely many solutions. Suppose we seek the sparsest solution, i.e., the one with the fewest nonzero entries: can it ever be unique? If so, when? As optimization of sparsity is combin ..."
Abstract - Cited by 427 (36 self) - Add to MetaCart
A full-rank matrix A ∈ IR n×m with n < m generates an underdetermined system of linear equations Ax = b having infinitely many solutions. Suppose we seek the sparsest solution, i.e., the one with the fewest nonzero entries: can it ever be unique? If so, when? As optimization of sparsity
Results 1 - 10 of 14,571