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Language Modeling Approach to Retrieval for SMS and FAQ Matching

机译：用于SMS和FAQ匹配的语言建模方法

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摘要

Short Messaging service popularly known as "SMS" has seen growth due to the growth in Mobile phone users. A mobile phone is considered as a cheap and easy device for communication. It is also used as a source to acquire and spread information. SMS based FAQ Retrieval task proposed in FIRE 2011 aims to provide the required information from frequently asked questions (FAQs). Challenge is to find a question from corpora of FAQs that best answers/matches with the SMS query. But, SMS queries are noisy as users tend to compress text by omitting letters, using slang, etc. This is observed due to a cap on the length of messages (160 characters constitute one SMS), lack of screen space (which makes reading large amounts of text difficult). In this paper, we propose a method using language modeling approach to match noisy SMS text with right FAQ. We extended this framework to match SMS queries with Cross-language FAQs. Results are promising for monolingual retrieval applied on English, Hindi and Malayalam languages.
机译：短消息服务（俗称“ SMS”）由于手机用户的增长而增长。移动电话被认为是用于通信的便宜且容易的设备。它还用作获取和传播信息的来源。 FIRE 2011中提出的基于SMS的FAQ检索任务旨在提供常见问题（FAQ）所需的信息。挑战是从常见问题集中找到一个与SMS查询最匹配/最匹配的问题。但是，SMS查询很嘈杂，因为用户倾向于通过省略字母，使用语等来压缩文本。这是由于消息长度的上限（160个字符构成一个SMS），缺少屏幕空间（这使得阅读较大）大量文字）。在本文中，我们提出了一种使用语言建模方法将嘈杂的SMS文本与常见的FAQ相匹配的方法。我们扩展了此框架，以将SMS查询与跨语言常见问题进行匹配。将结果应用于英语，印地语和马拉雅拉姆语的单语检索是有希望的。

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