文章基本信息

标题：Question Answering with Sub Graph Embeddings Analytics and Future Discussionss
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作者：Dr. Radhika Mamidi ; G.V.S Chaitanya ; Nunna Teja 等
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2016
卷号：7
期号：2
页码：56-60
语种：English
出版社：Ayushmaan Technologies
摘要：Past frameworks for regular dialect questions over complex connected datasets require the client to enter a complete and all around shaped question, and present the answers as crude arrangements of substances. Utilizing a component based punctuation with a full formal semantics, we have built up a framework that can bolster rich autosuggest, and to convey progressively created examination for every outcome that it returns. Question Answering (QA) frameworks are turning into the rousing model for the eventual fate of internet searchers. While, as of late, datasets fundamental QA frameworks have been elevated from unstructured datasets to organized datasets withsemantically exceedingly improved metadata, question noting frameworks are as yet confronting genuine difficulties and are along these lines not living up to clients’ desires. This paper gives a comprehensive knowledge of difficulties known so far for building QA frameworks, with an exceptional spotlight on utilizing organized knowledge (i.e. learning diagrams). It in this way helps scientists to effectively spot holes to load with their future exploration motivation.
关键词：Question Answering System;Research Challenge;Speech Interface;Query Understanding;Data Quality