NLP found helpful (at least for one text categorization task)

Authors:
Carl Sable;Kathleen McKeown;Kenneth W. Church
Affiliations:
Columbia University, New York, NY;Columbia University, New York, NY;AT&T Shannon Laboratory, Florham Park, NJ
Venue:
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Year:
2002

Citing 10
Cited 4

Term-weighting approaches in automatic text retrieval

Information Processing and Management: an International Journal
Automatic text processing: the transformation, analysis, and retrieval of information by computer

Automatic text processing: the transformation, analysis, and retrieval of information by computer
Using WordNet to disambiguate word senses for text retrieval

SIGIR '93 Proceedings of the 16th annual international ACM SIGIR conference on Research and development in information retrieval
Word sense disambiguation for free-text indexing using a massive semantic network

CIKM '93 Proceedings of the second international conference on Information and knowledge management
Translating collocations for bilingual lexicons: a statistical approach

Computational Linguistics
Experiments on using semantic distances between words in image caption retrieval

SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Retrieval from captioned image databases using natural language processing

Proceedings of the ninth international conference on Information and knowledge management
Natural Language Information Retrieval

Natural Language Information Retrieval
Information Retrieval

Information Retrieval
A stochastic parts program and noun phrase parser for unrestricted text

ANLC '88 Proceedings of the second conference on Applied natural language processing

Exploring text and image features to classify images in bioscience literature

BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Wikipedia-based semantic interpretation for natural language processing

Journal of Artificial Intelligence Research
Exploring text and image features to classify images in bioscience literature

LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
Query rewriting using monolingual statistical machine translation

Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Attempts to use natural language processing (NLP) for text categorization and information retrieval (IR) have had mixed results. Nevertheless, there is a strong intuition that NLP is important, at least for some tasks. In this paper, we discuss a task involving captioned images for which the subject and the predicate are critical. The usefulness of NLP for this task is established in two ways. In addition to the standard method of introducing a new system and comparing its performance with others in the literature, we also present evidence from experiments with human subjects showing that NLP generally improves speed and accuracy.