[1] Yu Shitao, Yuan Xiaojie, Shi Jianxing,. Knowledge presentation model for QnA web forums [J]. Journal of Southeast University (English Edition), 2007, 23 (3): 369-372. [doi:10.3969/j.issn.1003-7985.2007.03.012]
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Knowledge presentation model for QnA web forums(
)
问答网络论坛的知识表示模型
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 23
- Issue:
- 2007 3
- Page:
- 369-372
- Research Field:
- Computer Science and Engineering
- Publishing date:
- 2007-09-30
Info
- Title:
- Knowledge presentation model for QnA web forums
- 问答网络论坛的知识表示模型
- Author(s):
- Yu Shitao; Yuan Xiaojie; Shi Jianxing
- College of Information Technical Science, Nankai University, Tianjin 300071, China
- Keywords:
- QnA web forum; knowledge presentation; semantic link; statement model; knowledge confidence
- PACS:
- TP391
- DOI:
- 10.3969/j.issn.1003-7985.2007.03.012
- Abstract:
- For an extract description of threads information in question and answer(QnA)web forums, it is proposed to construct a QnA knowledge presentation model in the English language, and then an entire solution for the QnA knowledge system is presented, including data gathering, platform building and applications design.With pre-defined dictionary and grammatical analysis, the model draws semantic information, grammatical information and knowledge confidence into IR methods, in the form of statement sets and term sets with semantic links.Theoretical analysis shows that the statement model can provide an exact presentation for QnA knowledge, breaking through any limits from original QnA patterns and being adaptable to various query demands;the semantic links between terms can assist the statement model, in terms of deducing new from existing knowledge.The model makes use of both information retrieval(IR)and natural language processing(NLP)features, strengthening the knowledge presentation ability.Many knowledge-based applications built upon this model can be improved, providing better performance.
- 为精确描述问答网络论坛的主题信息, 提出构建面向英语自然语言的问答知识表示模型, 进而提出包括数据采集、平台搭建和应用设计在内的问答知识系统的完整解决方案.模型借助先验词典和自然语言语法分析方法, 将语义信息、语法信息和知识置信度引入信息检索技术, 并以语句模型集合和带有语义链接的标引项集合的形式表现出来.理论分析表明:语句模型能够突破原始问答模式限制, 精确表达知识陈述, 满足各种查询需求;标引项之间的语义链接则可辅助语句模型, 在现有知识基础上推导出新知识.模型同时应用了信息检索和自然语言处理特征, 增强了知识表达能力.诸多知识系统应用可在此模型上得到改善, 提供更好的性能.
References:
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Memo
- Memo:
- Biographies: Yu Shitao(1981—), male, graduate;Yuan Xiaojie(corresponding author), female, doctor, professor, yuanxj@nankai.edu.cn.