Work

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

Year: 2002

Type: conference-paper

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.

Source: Conference on Empirical Methods in Natural Language Processing (EMNLP)

DOI: 10.3115/1118693.1118716

Authors: Carl Sable, Kathleen McKeown, Kenneth W. Church

Institutions: Columbia University, AT&T (United States)

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W2152607144

FWCI: 0.415

Cites: 16

Cited by: 12

Related to: 10