Graph based Extractive Multi-document Summarizer for Malayalam-an Experiment
نویسنده
چکیده
Multidocument summarization is an automatic process to generate summary extract from multiple documents written about the same topic. Of the many summarization systems developed for English language, the graph based system is found to be more effective. This paper mainly focuses on a multidocument summarizing system for Malayalam Language which follows a graph based approach. The proposed model uses a weighted undirected graph to represent the documents. The significant sentences for the summary are selected by applying the Page Rank algorithm. Experimental results demonstrate the effectiveness of the proposed system.
منابع مشابه
Towards Coherent Multi-Document Summarization
This paper presents G-FLOW, a novel system for coherent extractive multi-document summarization (MDS).1 Where previous work on MDS considered sentence selection and ordering separately, G-FLOW introduces a joint model for selection and ordering that balances coherence and salience. G-FLOW’s core representation is a graph that approximates the discourse relations across sentences based on indica...
متن کاملEmpirical analysis of exploiting review helpfulness for extractive summarization of online reviews
We propose a novel unsupervised extractive approach for summarizing online reviews by exploiting review helpfulness ratings. In addition to using the helpfulness ratings for review-level filtering, we suggest using them as the supervision of a topic model for sentence-level content scoring. The proposed method is metadata-driven, requiring no human annotation, and generalizable to different kin...
متن کاملA Proposed Textual Graph Based Model for Arabic Multi-document Summarization
Text summarization task is still an active area of research in natural language preprocessing. Several methods that have been proposed in the literature to solve this task have presented mixed success. However, such methods developed in a multi-document Arabic text summarization are based on extractive summary and none of them is oriented to abstractive summary. This is due to the challenges of...
متن کاملMulti-Document Abstractive Summarization Using ILP Based Multi-Sentence Compression
Abstractive summarization is an ideal form of summarization since it can synthesize information from multiple documents to create concise informative summaries. In this work, we aim at developing an abstractive summarizer. First, our proposed approach identifies the most important document in the multi-document set. The sentences in the most important document are aligned to sentences in other ...
متن کاملA Hybrid Approach to Multi-document Summarization of Opinions in Reviews
We present a hybrid method to generate summaries of product and services reviews by combining natural language generation and salient sentence selection techniques. Our system, STARLET-H, receives as input textual reviews with associated rated topics, and produces as output a natural language document summarizing the opinions expressed in the reviews. STARLET-H operates as a hybrid abstractive/...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016