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Exploring Verb Frames for Sentence Simplification in Hindi


Introduction
認知的および心理学的研究
「文の複雑さに伴い、テキストを読み、理解する努力が増加する」と述べられている。

文の複雑さは、主に「語彙の複雑さ」と「構文の複雑さ」に分類することができる。
自然言語処理では、レキシコン、辞書、類義語辞典などの様々なリソースを利用する。 ⇨ 語彙の複雑さを処理することができる

構文の複雑さに対処するためには・・・
文の構造を分析し、適切な操作を適用して構造を単純化させる。

現代の機械翻訳システムは長くて複雑な文章を翻訳するのが困難である。

現代のパーサーは、長い文章の構文解析と長距離依存の特定が困難であり、課題である。

For Parsing, it has been shown by McDonald and Nivre(2007) that syntactic parsing of long sentence and Identifying long distance dependencies is still a challenging task for modern day parsers. So, it looks intuitive to break down the sentence into smaller parts and use the simplified sentences for the task of parsing and Machine translation. In case of Automatic summarization, after simplifying sentences, it is likely that the accuracy of sentence extraction based summarization systems improves as smaller units of information are being extracted. We present a rule based approach for sentence simplification in Hindi. Our proposed system takes a sentence and returns a set of simple sentences, smaller in length. We have taken care to produce sentences which keep the meaning close to the original sentence. This paper is structured as follows: In Section 2, we discuss the related works for sentence simplification. Section 3 talks about complex sentence. Section 4 describes the linguistic resources we used. In section 5, we discuss our algorithm. Section 6 outlines evaluation of the system. In section 7, results are being talked about. Section 8 gives the error analysis and in Section 9, we conclude and talk about future works in this area.

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