Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary.
Saved in:
| Title: | Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary. |
|---|---|
| Authors: | Dorji, Tshering1 cigay@is.tokushima-u.ac.jp, Atlam, El-sayed1 atlam@is.tokushima-u.ac.jp, Yata, Susumu1 yata@is.tokushima-u.ac.jp, Fuketa, Masao1 fuketa@is.tokushima-u.ac.jp, Morita, Kazuhiro1 kam@is.tokushima-u.ac.jp, Aoe, Jun-ichi1 aoe@is.tokushima-u.ac.jp |
| Source: | Knowledge & Information Systems. Apr2011, Vol. 27 Issue 1, p141-161. 21p. 3 Diagrams, 6 Charts. |
| Subjects: | Document selection, Terms & phrases, Extraction (Linguistics), Encyclopedias & dictionaries, Wikipedia |
| Abstract: | Field Association (FA) Terms-words or phrases that serve to identify document fields are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract and select relevant FA Terms to build a comprehensive dictionary of FA Terms. This paper presents a new method to extract, select and rank FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules, corpora comparison and modified tf-idf weighting. Experimental evaluation on 21 fields using 306 MB of domain-specific corpora obtained from English Wikipedia dumps selected up to 2,517 FA Terms (single and compound) per field at precision and recall of 74-97 and 65-98. This is better than the traditional methods. The FA Terms dictionary constructed using this method achieved an average accuracy of 97.6% in identifying the fields of 10,077 test documents collected from Wikipedia, Reuters RCV1 corpus and 20 Newsgroup data set. [ABSTRACT FROM AUTHOR] |
| Copyright of Knowledge & Information Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 59595121 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Dorji%2C+Tshering%22">Dorji, Tshering</searchLink><relatesTo>1</relatesTo><i> cigay@is.tokushima-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Atlam%2C+El-sayed%22">Atlam, El-sayed</searchLink><relatesTo>1</relatesTo><i> atlam@is.tokushima-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Yata%2C+Susumu%22">Yata, Susumu</searchLink><relatesTo>1</relatesTo><i> yata@is.tokushima-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Fuketa%2C+Masao%22">Fuketa, Masao</searchLink><relatesTo>1</relatesTo><i> fuketa@is.tokushima-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Morita%2C+Kazuhiro%22">Morita, Kazuhiro</searchLink><relatesTo>1</relatesTo><i> kam@is.tokushima-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Aoe%2C+Jun-ichi%22">Aoe, Jun-ichi</searchLink><relatesTo>1</relatesTo><i> aoe@is.tokushima-u.ac.jp</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Knowledge+%26+Information+Systems%22">Knowledge & Information Systems</searchLink>. Apr2011, Vol. 27 Issue 1, p141-161. 21p. 3 Diagrams, 6 Charts. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Document+selection%22">Document selection</searchLink><br /><searchLink fieldCode="DE" term="%22Terms+%26+phrases%22">Terms & phrases</searchLink><br /><searchLink fieldCode="DE" term="%22Extraction+%28Linguistics%29%22">Extraction (Linguistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Encyclopedias+%26+dictionaries%22">Encyclopedias & dictionaries</searchLink><br /><searchLink fieldCode="DE" term="%22Wikipedia%22">Wikipedia</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Field Association (FA) Terms-words or phrases that serve to identify document fields are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract and select relevant FA Terms to build a comprehensive dictionary of FA Terms. This paper presents a new method to extract, select and rank FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules, corpora comparison and modified tf-idf weighting. Experimental evaluation on 21 fields using 306 MB of domain-specific corpora obtained from English Wikipedia dumps selected up to 2,517 FA Terms (single and compound) per field at precision and recall of 74-97 and 65-98. This is better than the traditional methods. The FA Terms dictionary constructed using this method achieved an average accuracy of 97.6% in identifying the fields of 10,077 test documents collected from Wikipedia, Reuters RCV1 corpus and 20 Newsgroup data set. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Knowledge & Information Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=59595121 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10115-010-0296-x Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 141 Subjects: – SubjectFull: Document selection Type: general – SubjectFull: Terms & phrases Type: general – SubjectFull: Extraction (Linguistics) Type: general – SubjectFull: Encyclopedias & dictionaries Type: general – SubjectFull: Wikipedia Type: general Titles: – TitleFull: Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Dorji, Tshering – PersonEntity: Name: NameFull: Atlam, El-sayed – PersonEntity: Name: NameFull: Yata, Susumu – PersonEntity: Name: NameFull: Fuketa, Masao – PersonEntity: Name: NameFull: Morita, Kazuhiro – PersonEntity: Name: NameFull: Aoe, Jun-ichi IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2011 Type: published Y: 2011 Identifiers: – Type: issn-print Value: 02191377 Numbering: – Type: volume Value: 27 – Type: issue Value: 1 Titles: – TitleFull: Knowledge & Information Systems Type: main |
| ResultId | 1 |
