A language independent approach to multilingual text summarization
نویسندگان
چکیده
This paper describes an efficient algorithm for language independent generic extractive summarization for single document. The algorithm is based on structural and statistical (rather than semantic) factors. Through evaluations performed on a single-document summarization for English, Hindi, Gujarati and Urdu documents, we show that the method performs equally well regardless of the language. The algorithm has been applied on DUC data for English documents and various newspaper articles for other languages with corresponding stop words list and modified stemmer. The results of summarization have been compared with DUC 2002 data using degree of representativeness. For other languages, the degree of representativeness we get is highly encouraging.
منابع مشابه
MUSE – A Multilingual Sentence Extractor
MUltilingual Sentence Extractor (MUSE) is aimed at multilingual single-document summarization. MUSE implements the supervised language-independent summarization approach based on optimization of multiple statistical sentence ranking methods. The MUSE tool consists of two main modules: the training module activated in the offline mode, and the on-line summarization module. The training module ca...
متن کاملA survey on Automatic Text Summarization
Text summarization endeavors to produce a summary version of a text, while maintaining the original ideas. The textual content on the web, in particular, is growing at an exponential rate. The ability to decipher through such massive amount of data, in order to extract the useful information, is a major undertaking and requires an automatic mechanism to aid with the extant repository of informa...
متن کاملMultilingual Single-Document Summarization with MUSE
MUltilingual Sentence Extractor (MUSE) is aimed at multilingual single-document summarization. MUSE implements a supervised language-independent summarization approach based on optimization of multiple sentence ranking methods using a Genetic Algorithm. The main advantage of MUSE is its language-independency – it is using statistical sentence features, which can be calculated for sentences in a...
متن کاملAllSummarizer system at MultiLing 2015: Multilingual single and multi-document summarization
In this paper, we evaluate our automatic text summarization system in multilingual context. We participated in both single document and multi-document summarization tasks of MultiLing 2015 workshop. Our method involves clustering the document sentences into topics using a fuzzy clustering algorithm. Then each sentence is scored according to how well it covers the various topics. This is done us...
متن کاملMultilingual Natural Language Generation within Abstractive Summarization
With the tremendous amount of textual data available in the Internet, techniques for abstractive text summarization become increasingly appreciated. In this paper, we present work in progress that tackles the problem of multilingual text summarization using semantic representations. Our system is based on abstract linguistic structures obtained from an analysis pipeline of disambiguation, synta...
متن کامل