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The Impact of Multifaceted Tagging on Learning Tag Relations and Search

by Fabian Abel, Nicola Henze, Ricardo Kawase, Daniel Krause
"... Abstract. In this paper we present a model for multifaceted tagging, i.e. tagging enriched with contextual information. We present TagMe!, a social tagging front-end for Flickr images, that provides multifaceted tagging functionality: It enables users to attach tag assignments to a specific area wit ..."
Abstract - Cited by 5 (5 self) - Add to MetaCart
the performance of FolkRank-based search. Further, we demonstrate the benefits of TagMe! tagging facets for learning semantics within folksonomies. 1

Text Chunking using Transformation-Based Learning

by Lance A. Ramshaw, Mitchell P. Marcus , 1995
"... Eric Brill introduced transformation-based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks. For ..."
Abstract - Cited by 509 (0 self) - Add to MetaCart
Eric Brill introduced transformation-based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks

Machine Learning in Automated Text Categorization

by Fabrizio Sebastiani - ACM COMPUTING SURVEYS , 2002
"... The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this p ..."
Abstract - Cited by 1658 (22 self) - Add to MetaCart
to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual

Inductive Learning Algorithms and Representations for Text Categorization

by Susan Dumais, John Platt, Mehran Sahami, David Heckerman , 1998
"... Text categorization – the assignment of natural language texts to one or more predefined categories based on their content – is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text categori ..."
Abstract - Cited by 641 (8 self) - Add to MetaCart
Text categorization – the assignment of natural language texts to one or more predefined categories based on their content – is an important component in many information organization and management tasks. We compare the effectiveness of five different automatic learning algorithms for text

The Elements of Statistical Learning -- Data Mining, Inference, and Prediction

by Trevor Hastie, Robert Tibshirani, Jerome Friedman
"... ..."
Abstract - Cited by 1320 (13 self) - Add to MetaCart
Abstract not found

The Proposition Bank: An Annotated Corpus of Semantic Roles

by Martha Palmer, Paul Kingsbury, Daniel Gildea - Computational Linguistics , 2005
"... The Proposition Bank project takes a practical approach to semantic representation, adding a layer of predicate-argument information, or semantic role labels, to the syntactic structures of the Penn Treebank. The resulting resource can be thought of as shallow, in that it does not represent corefere ..."
Abstract - Cited by 536 (21 self) - Add to MetaCart
and to analyze the frequency of syntactic/semantic alternations in the corpus. We describe an automatic system for semantic role tagging trained on the corpus and discuss the effect on its performance of various types of information, including a comparison of full syntactic parsing with a flat representation

TnT - A Statistical Part-Of-Speech Tagger

by Thorsten Brants , 2000
"... Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison h ..."
Abstract - Cited by 525 (5 self) - Add to MetaCart
Trigrams'n'Tags (TnT) is an efficient statistical part-of-speech tagger. Contrary to claims found elsewhere in the literature, we argue that a tagger based on Markov models performs at least as well as other current approaches, including the Maximum Entropy framework. A recent comparison

Transfer of Cognitive Skill

by John R. Anderson , 1989
"... A framework for skill acquisition is proposed that includes two major stages in the development of a cognitive skill: a declarative stage in which facts about the skill domain are interpreted and a procedural stage in which the domain knowledge is directly embodied in procedures for performing the s ..."
Abstract - Cited by 869 (21 self) - Add to MetaCart
. The psychology of human learning has been very thin in ideas about what happens to skills under the impact of this amount of learning—and for obvious reasons. This article presents a theory about the changes in the nature of a skill over such large time scales and about the basic learning processes

Extracting Relations from Large Plain-Text Collections

by Eugene Agichtein, Luis Gravano , 2000
"... Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering precise queries or for running data mining tasks. We explore a technique for extracting such tables fr ..."
Abstract - Cited by 480 (25 self) - Add to MetaCart
Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering precise queries or for running data mining tasks. We explore a technique for extracting such tables

Generating typed dependency parses from phrase structure parses

by Marie-Catherine de Marneffe, Bill MacCartney, Christopher D. Manning - IN PROC. INT’L CONF. ON LANGUAGE RESOURCES AND EVALUATION (LREC , 2006
"... This paper describes a system for extracting typed dependency parses of English sentences from phrase structure parses. In order to capture inherent relations occurring in corpus texts that can be critical in real-world applications, many NP relations are included in the set of grammatical relations ..."
Abstract - Cited by 636 (25 self) - Add to MetaCart
This paper describes a system for extracting typed dependency parses of English sentences from phrase structure parses. In order to capture inherent relations occurring in corpus texts that can be critical in real-world applications, many NP relations are included in the set of grammatical
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