A Hindi Question Answering system for E-learning documents

P. Kumar, S. Kashyap, A. Mittal, S. Gupta
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引用次数: 21

Abstract

To empower the general mass through access to information and knowledge, organized efforts are being made to develop relevant content in local languages and provide local language capabilities to utility software. We have developed a question answering (QA) system for Hindi documents that would be relevant for masses using Hindi as the primary language of education. The user should be able to access information from e-learning documents in a user friendly way, that is by questioning the system in their native language Hindi and the system returns the intended answer (also in Hindi) by searching in context from the repository of Hindi documents. The language constructs, query structure, common words, etc. are completely different in Hindi as compared to English. A novel strategy, in addition to conventional search and NLP techniques, was used to construct the Hindi QA system. The focus is on context based retrieval of information. For this purpose we implemented a Hindi search engine that works on locality-based similarity heuristics to retrieve relevant passages from the collection. It also incorporates language analysis modules like stemmer and morphological analyzer as well as self constructed lexical database of synonyms. The experimental results over corpus of two important domains of agriculture and science show effectiveness of our approach
用于电子学习文档的印地语问答系统
为了通过获取信息和知识使广大群众获得权力,正在作出有组织的努力,以当地语文编写有关内容,并提供实用软件的当地语文能力。我们为印地语文档开发了一个问答(QA)系统,这将与使用印地语作为主要教育语言的大众相关。用户应该能够以用户友好的方式访问电子学习文档中的信息,即用他们的母语印地语向系统提问,系统通过在上下文中搜索印地语文档存储库,返回预期的答案(也是印地语)。与英语相比,印地语的语言结构、查询结构、常用词等都完全不同。除了传统的搜索和NLP技术外,还采用了一种新的策略来构建印地语问答系统。重点是基于上下文的信息检索。为此,我们实现了一个印地语搜索引擎,它使用基于位置的相似性启发式方法从集合中检索相关段落。它还集成了词干分析、词形分析等语言分析模块,以及自构建的同义词词汇数据库。在农业和科学两个重要领域的语料库上的实验结果表明了该方法的有效性
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