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Ahead Context Qa: Interactive Communications Spawning Through Accumulation Propaganda

机译:提前上下文QA:通过累积宣传产卵的交互式通信

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Interactively freak out information to the user is generally play a vital role. Existent QA is usually enough to be useful only in plain text format providing to the user. In this project we connote textual data with the appropriate media to recommend a inspired by the response. It has three components of our system Construal median scrap, Inquiry localization, Data pick up and Launch. The Construal median scrap is used to select a variety of responses to the receiver. Inquiry localization is used for extracting keywords from the source in question is widely used in the investigation. Data pick up and Launch is used for choose the correct answer and the result is used to retrieve the data and launching. We use Stemming algorithm,Naive Bayes classifier algorithm and Ranking algorithm. We will increase the contribution of community responses. Data unwittingly, any user can get information immediately. Our nigh is to deal with complicated questions. Queries are generated on the basis of the information we collect upright multimedia image and video with multimedia search engines.
机译:对用户的交互方式信息通常发挥重要作用。存在的Qa通常足以仅以纯文本格式提供给用户。在这个项目中,我们将文本数据与适当的媒体表示,建议由响应的启发。它有三个组成的我们的系统构建中位数废料,查询本地化,数据拾取和启动。 Construal中值Scap用于为接收器选择各种响应。询问本地化用于从有问题的来源中提取关键字被广泛用于调查。数据拾取和启动用于选择正确的答案,结果用于检索数据和启动。我们使用Stemming算法,天真贝叶斯分类器算法和排名算法。我们将增加社区反应的贡献。数据不知不觉,任何用户都可以立即获取信息。我们的Nigh是为了处理复杂的问题。基于我们收集直立多媒体图像和视频的信息,生成查询。

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