Abstract
Multilingual knowledge sharing imposes new requirements on knowledge management systems so as to present digital knowledge resources in multiple languages. Knowledge sharing is degraded by inconsistencies such as contents omitted or altered in one of the languages. To resolve this issue, we present a mechanism for detecting inconsistencies in multilingual knowledge sharing. A state transition model is proposed to define the states of the multilingual contents,the set of actions, and the set of transition functions. Inconsistency detection rules are designed to represent the states of the multilingual contents and thus permit the identification of inconsistencies in knowledge sharing. The analysis of a multilingual Wikipedia article indicates that inconsistencies are present in multilingual contents generated by collaboration. In experiments, the proposed mechanism is applied to a test set of revision histories of multilingual articles; the outcome shows satisfactory results with an average precision of 88% in detecting inconsistencies and a recall of86%. While the proposal considers only user edit actions, it can detect inconsistencies which will be useful in allowing Natural Language Processing (NLP) based systems to synchronize multilingual contents in an early phase.
| Original language | English |
|---|---|
| Article number | 1450033 |
| Journal | Journal of Information and Knowledge Management |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2014 Dec 12 |
| Externally published | Yes |
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Keywords
- collaboration
- inconsistency detection
- Knowledge sharing
- multilingual content
- multilingual Wikipedia
ASJC Scopus subject areas
- Computer Science Applications
- Computer Networks and Communications
- Library and Information Sciences
Cite this
Inconsistency Detection in Multilingual Knowledge Sharing. / Pariyar, Amit; Murakami, Yohei; Lin, Donghui; Ishida, Toru.
In: Journal of Information and Knowledge Management, Vol. 13, No. 4, 1450033, 12.12.2014.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Inconsistency Detection in Multilingual Knowledge Sharing
AU - Pariyar, Amit
AU - Murakami, Yohei
AU - Lin, Donghui
AU - Ishida, Toru
PY - 2014/12/12
Y1 - 2014/12/12
N2 - Multilingual knowledge sharing imposes new requirements on knowledge management systems so as to present digital knowledge resources in multiple languages. Knowledge sharing is degraded by inconsistencies such as contents omitted or altered in one of the languages. To resolve this issue, we present a mechanism for detecting inconsistencies in multilingual knowledge sharing. A state transition model is proposed to define the states of the multilingual contents,the set of actions, and the set of transition functions. Inconsistency detection rules are designed to represent the states of the multilingual contents and thus permit the identification of inconsistencies in knowledge sharing. The analysis of a multilingual Wikipedia article indicates that inconsistencies are present in multilingual contents generated by collaboration. In experiments, the proposed mechanism is applied to a test set of revision histories of multilingual articles; the outcome shows satisfactory results with an average precision of 88% in detecting inconsistencies and a recall of86%. While the proposal considers only user edit actions, it can detect inconsistencies which will be useful in allowing Natural Language Processing (NLP) based systems to synchronize multilingual contents in an early phase.
AB - Multilingual knowledge sharing imposes new requirements on knowledge management systems so as to present digital knowledge resources in multiple languages. Knowledge sharing is degraded by inconsistencies such as contents omitted or altered in one of the languages. To resolve this issue, we present a mechanism for detecting inconsistencies in multilingual knowledge sharing. A state transition model is proposed to define the states of the multilingual contents,the set of actions, and the set of transition functions. Inconsistency detection rules are designed to represent the states of the multilingual contents and thus permit the identification of inconsistencies in knowledge sharing. The analysis of a multilingual Wikipedia article indicates that inconsistencies are present in multilingual contents generated by collaboration. In experiments, the proposed mechanism is applied to a test set of revision histories of multilingual articles; the outcome shows satisfactory results with an average precision of 88% in detecting inconsistencies and a recall of86%. While the proposal considers only user edit actions, it can detect inconsistencies which will be useful in allowing Natural Language Processing (NLP) based systems to synchronize multilingual contents in an early phase.
KW - collaboration
KW - inconsistency detection
KW - Knowledge sharing
KW - multilingual content
KW - multilingual Wikipedia
UR - http://www.scopus.com/inward/record.url?scp=84941267664&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84941267664&partnerID=8YFLogxK
U2 - 10.1142/S0219649214500336
DO - 10.1142/S0219649214500336
M3 - Article
AN - SCOPUS:84941267664
VL - 13
JO - Journal of Information and Knowledge Management
JF - Journal of Information and Knowledge Management
SN - 0219-6492
IS - 4
M1 - 1450033
ER -