Title
Retrieving Nasa Problem Reports With Natural Language
Abstract
A system that retrieves problem reports from a NASA database is described. The database is queried with natural language questions. Part-of-speech tags are first assigned to each word in the question using a rule-based tagger. A partial parse of the question is then produced with independent sets of deterministic finite state automata. Using partial parse information, a look up strategy searches the database for problem reports relevant to the question. A bigram stemmer and irregular verb conjugates have been incorporated into the system to improve accuracy. The system is evaluated by a set of fifty five questions posed by NASA engineers. A discussion of future research is also presented.
Publication Date
1-1-2002
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
2553
Number of Pages
150-159
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/3-540-36271-1_13
Copyright Status
Unknown
Socpus ID
84957802227 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84957802227
STARS Citation
van Delden, Sebastian and Gomez, Fernando, "Retrieving Nasa Problem Reports With Natural Language" (2002). Scopus Export 2000s. 2679.
https://stars.library.ucf.edu/scopus2000/2679