Paper Info
Title
Natural language processing in support of decision-making: phrases and part-of-speech tagging
Abstract
The use of natural language information can improve decision-making. Darwinian considerations suggest that language may have developed because it leads to improved decision-making and survival, justifying the study of language's contribution to decision-making. The study of information-based decision-making within the context of evolution provides a view of information use that allows us to both describe the phenomenon of information use as well as to explain why an information use occurs as it does. Increasing information retrieval performance using phrases and part-of-speech (POS) information is one example of a type of decision-making performance that is improved when using this linguistic information. By studying a set of phrases used in a text retrieval system, we are able to show the relative effectiveness of using multi-term phrases as opposed to individual terms, as well as the relative worth of POS tagged terms or phrases, as opposed to untagged terms or phrases. An explanation is suggested for why POS tags contribute less to higher order grammatical constructs. We propose a measure of those needs for POS disambiguation that can be addressed by tagging; some example terms are analyzed using this measure, and specific degrees of ambiguity are proposed.
Year
DOI
Venue
2001
10.1016/S0306-4573(00)00061-3
Inf. Process. Manage.
Keywords
Field
DocType
natural language processing,part-of-speech tagging,knowledge representation,relevance information retrieval,higher order,information systems,part of speech,natural language,information retrieval
Information system,Knowledge representation and reasoning,Information retrieval,Information seeking,Computer science,Phrase,Natural language,Natural language processing,Relevance (information retrieval),Artificial intelligence,Sentence,Ambiguity
Journal
Volume
Issue
ISSN
37
6
Information Processing and Management
Citations 
PageRank 
References 
8
0.63
22
Authors
1
Name
Order
Citations
PageRank
Robert M. Losee127636.01