Consistency analysis in multi-language knowledge sharing system

Amit Pariyar*, Yohei Murakami, Donghui Lin, Toru Ishida

*この研究の対応する著者

研究成果: Chapter

抄録

Unprecedented growth in knowledge sharing among multi-language communities, both common and distinct languages, has raised the possibility of sharing inconsistent content. Though popular with traditional system, the approach to explicitly state consistency rules to avoid inconsistency is practically not suited for multi-language knowledge sharing system because of sheer complexity. Alternatively this chapter focuses on potential cause of inconsistency, cases such as content omitted, content updates not propagated and content conflicts. Ignoring such cases in knowledge sharing has undesirable consequences: community bias, global and local inconsistency and regional discrepancies. Consistency constraints from opposing knowledge sharing goals among communities is another issue. Due to which consistency policy ranges from rigid ‘one to one consistency’ to non-rigid ‘consistency where needed’. This chapter contributes with (a) process-based approach for multilingual content synchronization to leverage knowledge equally and (b) propagation-based approach to analyze community preferences when sharing specific content categories/geographic regions, to customize knowledge sharing; a value add-on to designing language services adhering to knowledge sharing goals.

本文言語English
ホスト出版物のタイトルCognitive Technologies
出版社Springer Verlag
ページ141-156
ページ数16
9789811077920
DOI
出版ステータスPublished - 2018
外部発表はい

出版物シリーズ

名前Cognitive Technologies
番号9789811077920
ISSN(印刷版)1611-2482

ASJC Scopus subject areas

  • ソフトウェア
  • 人工知能

フィンガープリント

「Consistency analysis in multi-language knowledge sharing system」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル