Extracting Primary Information Requests from Query Messages by Partial Discourse Processing
Summary :
This paper develops an efficient mechanism for extracting primary information requests from 'Seek-Object' type query messages. The mechanism consists of three steps. The first step extracts sentences which signal that the query is 'Seek-Object' type by recognizing distinctive surface expressions. The second step, biased by the expression patterns, analyzes their internal structures. The third step integrates these fragments by a partial discourse processing and represents writers' goal-directed information request; as these sentences often include referential expressions and the referred expressions are in background goal descriptions. We claim the mechanism can extract information requests fairly accurately, by showing evaluation results.
- Publication
- IEICE TRANSACTIONS on Information Vol.E79-D No.9 pp.1344-1352
- Publication Date
- 1996/09/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- PAPER
- Category
- Artificial Intelligence and Cognitive Science
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Yoshihiko HAYASHI, "Extracting Primary Information Requests from Query Messages by Partial Discourse Processing" in IEICE TRANSACTIONS on Information,
vol. E79-D, no. 9, pp. 1344-1352, September 1996, doi: .
Abstract: This paper develops an efficient mechanism for extracting primary information requests from 'Seek-Object' type query messages. The mechanism consists of three steps. The first step extracts sentences which signal that the query is 'Seek-Object' type by recognizing distinctive surface expressions. The second step, biased by the expression patterns, analyzes their internal structures. The third step integrates these fragments by a partial discourse processing and represents writers' goal-directed information request; as these sentences often include referential expressions and the referred expressions are in background goal descriptions. We claim the mechanism can extract information requests fairly accurately, by showing evaluation results.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_9_1344/_p
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@ARTICLE{e79-d_9_1344,
author={Yoshihiko HAYASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Extracting Primary Information Requests from Query Messages by Partial Discourse Processing},
year={1996},
volume={E79-D},
number={9},
pages={1344-1352},
abstract={This paper develops an efficient mechanism for extracting primary information requests from 'Seek-Object' type query messages. The mechanism consists of three steps. The first step extracts sentences which signal that the query is 'Seek-Object' type by recognizing distinctive surface expressions. The second step, biased by the expression patterns, analyzes their internal structures. The third step integrates these fragments by a partial discourse processing and represents writers' goal-directed information request; as these sentences often include referential expressions and the referred expressions are in background goal descriptions. We claim the mechanism can extract information requests fairly accurately, by showing evaluation results.},
keywords={},
doi={},
ISSN={},
month={September},}
Copy
TY - JOUR
TI - Extracting Primary Information Requests from Query Messages by Partial Discourse Processing
T2 - IEICE TRANSACTIONS on Information
SP - 1344
EP - 1352
AU - Yoshihiko HAYASHI
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 1996
AB - This paper develops an efficient mechanism for extracting primary information requests from 'Seek-Object' type query messages. The mechanism consists of three steps. The first step extracts sentences which signal that the query is 'Seek-Object' type by recognizing distinctive surface expressions. The second step, biased by the expression patterns, analyzes their internal structures. The third step integrates these fragments by a partial discourse processing and represents writers' goal-directed information request; as these sentences often include referential expressions and the referred expressions are in background goal descriptions. We claim the mechanism can extract information requests fairly accurately, by showing evaluation results.
ER -
English
