KFU. Card publication. Extracting Composite Summaries from Qualitative Data

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

EXTRACTING COMPOSITE SUMMARIES FROM QUALITATIVE DATA

Form of presentation

Conference proceedings in international journals and collections

Year of publication

2021

Authors, employees of KFU

Zuev Denis Sergeevich, author

Other authors

Authors, postgraduates KFU

Rodriges Rodriges Karlos Rafael , postgraduate kfu

Bibliographic description in the original language

Rodríguez C.R.R., Abreu M.P., Zuev D.S. (2021) Extracting Composite Summaries from Qualitative Data. In: Hernández Heredia Y., Milián Núñez V., Ruiz Shulcloper J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2021. Lecture Notes in Computer Science, vol 13055. Springer, Cham. https://doi.org/10.1007/978-3-030-89691-1_26

Annotation

The paper proposes a model combining association rules and elements of Rhetorical Structure Theory (RST) to generate composite linguistic summaries from qualitative data. The specifications of three new abstract forms of composite linguistic summaries for qualitative data are presented. The proposed abstract forms represent relations of Evidence, Contrast, and Emphasis inspired by RST, consisting of at least two semantically related constituent statements linked by a connector specific to each relation. The constituent statements have the structure of the classical protoforms of linguistic summaries, which in this paper are built from an association rule, to which a fuzzy linguistic quantifier is assigned. Moreover, the definitions of truth degree, relation strength, and coverage degree for composite relations are presented. The model applicability was checked through a use case performed with a database of 2128 cases of the Economic Chamber of the Provincial People?s Court of Havana.

Keywords

Association rules, Linguistic descriptions of data, Linguistic data summarization, Rhetorical structure theory

Place of publication

Cham

Publishing house

Springer

URL

https://doi.org/10.1007/978-3-030-89691-1_26

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=260493&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Zuev Denis Sergeevich	ru_RU
dc.contributor.author	Rodriges Rodriges Karlos Rafael	ru_RU
dc.date.accessioned	2021-01-01T00:00:00Z	ru_RU
dc.date.available	2021-01-01T00:00:00Z	ru_RU
dc.date.issued	2021	ru_RU
dc.identifier.citation	Rodríguez C.R.R., Abreu M.P., Zuev D.S. (2021) Extracting Composite Summaries from Qualitative Data. In: Hernández Heredia Y., Milián Núñez V., Ruiz Shulcloper J. (eds) Progress in Artificial Intelligence and Pattern Recognition. IWAIPR 2021. Lecture Notes in Computer Science, vol 13055. Springer, Cham. https://doi.org/10.1007/978-3-030-89691-1_26	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=260493&p_lang=2	ru_RU
dc.description.abstract	The paper proposes a model combining association rules and elements of Rhetorical Structure Theory (RST) to generate composite linguistic summaries from qualitative data. The specifications of three new abstract forms of composite linguistic summaries for qualitative data are presented. The proposed abstract forms represent relations of Evidence, Contrast, and Emphasis inspired by RST, consisting of at least two semantically related constituent statements linked by a connector specific to each relation. The constituent statements have the structure of the classical protoforms of linguistic summaries, which in this paper are built from an association rule, to which a fuzzy linguistic quantifier is assigned. Moreover, the definitions of truth degree, relation strength, and coverage degree for composite relations are presented. The model applicability was checked through a use case performed with a database of 2128 cases of the Economic Chamber of the Provincial People?s Court of Havana.	ru_RU
dc.language.iso	ru	ru_RU
dc.publisher	Springer	ru_RU
dc.subject	Association rules	ru_RU
dc.subject	Linguistic descriptions of data	ru_RU
dc.subject	Linguistic data summarization	ru_RU
dc.subject	Rhetorical structure theory	ru_RU
dc.title	Extracting Composite Summaries from Qualitative Data	ru_RU
dc.type	Conference proceedings in international journals and collections	ru_RU