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A Novel Relational Learning-to-Rank Approach for Topic-Focused Multi-document Summarization

Yadong Zhu, Yanyan Lan, Jiafeng Guo, Pan Du, Xueqi Cheng
2013 2013 IEEE 13th International Conference on Data Mining  
Topic-focused multi-document summarization aims to produce a summary over a set of documents and conveys the most important aspects of a given topic.  ...  In this paper, we propose a novel relational learning-to-rank approach (R-LTR) to solve this problem.  ...  CONCLUSION In this paper, we propose a novel relational learning-torank approach for the task of topic-focused multi-document summarization.  ... 
doi:10.1109/icdm.2013.38 dblp:conf/icdm/ZhuLGDC13 fatcat:hpv7jepkxzcgnozqewie2j4twu

Supervised Lazy Random Walk for Topic-Focused Multi-document Summarization

Pan Du, Jiafeng Guo, Xueqi Cheng
2011 2011 IEEE 11th International Conference on Data Mining  
Topic-focused multi-document summarization aims to produce a summary given a specific topic description and a set of related documents.  ...  Moreover, our approach can achieve the three major goals of topic-focused multi-document summarization (i.e. relevance, salience and diversity) simultaneously with a unified ranking process.  ...  In this paper, we propose a novel extractive approach based on supervised lazy random walk (SuperLazy) for topic-focused multi-document summarization.  ... 
doi:10.1109/icdm.2011.140 dblp:conf/icdm/DuGC11 fatcat:mtebz3hhl5bx7m5k7gr3dkku74

Query-focused Multi-document Summarization: Combining a Novel Topic Model with Graph-based Semi-supervised Learning [article]

Jiwei Li, Sujian Li
2013 arXiv   pre-print
Graph-based semi-supervised learning has proven to be an effective approach for query-focused multi-document summarization.  ...  Inspired by previous researches, we propose a two-layer (i.e. sentence layer and topic layer) graph-based semi-supervised learning approach.  ...  for query-focused multi-document summarization.  ... 
arXiv:1212.2036v3 fatcat:sigpxdsgybhfva3wjzvnufxas4

Topic analysis for topic-focused multi-document summarization

Xiaojun Wan
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
Topic-focused multi-document summarization aims to produce a summary biased to a given topic or user profile.  ...  This paper presents a novel extractive approach based on manifold-ranking of sentences to this summarization task.  ...  In this study, we propose a novel extractive approach based on manifold-ranking [Zhou et al., 2003a; Zhou et al., 2003b] of sentences to topic-focused multi-document summarization.  ... 
doi:10.1145/1645953.1646184 dblp:conf/cikm/Wan09 fatcat:hgsvn4lsajht5l5k74mfo3jgdq

A Contextual Query Expansion Based Multi-document Summarizer for Smart Learning

Guangbing Yang, Kinshuk, Dunwei Wen, Erkki Sutinen
2013 2013 International Conference on Signal-Image Technology & Internet-Based Systems  
In our approach, a multi-document summarization system is built upon a topical n-grams model with a query expansion algorithm to capture the contextual information conveyed by word order and abstract topics  ...  in documents for enhancing sentence ranking in text summarization.  ...  ACKNOWLEDGMENT This research was supported by the NSERC, iCORE, Xerox, and the research related funding by Mr. A. Markin.  ... 
doi:10.1109/sitis.2013.163 dblp:conf/sitis/YangKWS13 fatcat:5xrwnuzwf5f2fkw4n36sxch5ly

An Overview of Text Summarization

Laxmi B., P. Venkata
2017 International Journal of Computer Applications  
This paper presents a comprehensive survey of contemporary text summarization of extractive and abstractive approaches.  ...  Automatic text summarization system produces a summary, i.e. short length text that includes all the significant information for the article.  ...  In specific, they propose a novel approach for graph based text ranking, with improved results comparative to existing ranking algorithms.  ... 
doi:10.5120/ijca2017915109 fatcat:hlpvgrzpd5hord5bfy4zndqexi

Automatic Multi Document Summarization Approaches

Kumar
2012 Journal of Computer Science  
With the aim of enhancing multi document summarization, specifically news documents, a novel type of approach is outlined to be developed in the future, taking into account the generic components of a  ...  Results: In this study, some survey on multi document summarization approaches has been presented.  ...  At the end of this study, a novel type of approach is outlined to be developed in the future, for news documents summarization.  ... 
doi:10.3844/jcssp.2012.133.140 fatcat:6wry32zaufczbkm7f62nor5ipq

Topic-sensitive multi-document summarization algorithm

Liu Na, Tang Di, Lu Ying, Tang Xiao-Jun, Wang Hai-Wen
2015 Computer Science and Information Systems  
Some of the topics can be a collection of irrelevant words or represent insignificant themes. This paper proposed a topic-sensitive algorithm for multi-document summarization.  ...  Each topic is measured by three different LDA criteria. Significance topic is evaluated by using weight linear combination to combine the multi-criteria.  ...  Zhu Y presented a novel relational learning-to-rank approach for topic-focused multi-document summarization in 2013.  ... 
doi:10.2298/csis140815060n fatcat:qkeaeycbd5cy7mdmiikwmzyd5y

A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization

Jiwei Li, Sujian Li
2013 Transactions of the Association for Computational Linguistics  
Supervised learning methods and LDA based topic model have been successfully applied in the field of multi-document summarization.  ...  In this paper, we propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic models in a principled way, thus taking advantages of both topic model and feature  ...  We also thank the three anonymous reviewers for their helpful comments. Corresponding author: Sujian Li.  ... 
doi:10.1162/tacl_a_00212 fatcat:dcbvuhvbmbfjvl5f2rxyaieety

AdaSum

Jin Zhang, Xueqi Cheng, Gaowei Wu, Hongbo Xu
2008 Proceeding of the 17th ACM conference on Information and knowledge mining - CIKM '08  
Topic representation mismatch is a key problem in topic-oriented summarization for the specified topic is usually too short to understand/interpret.  ...  Furthermore, a linear combination of base summarizers is proposed to further reduce the topic representation mismatch from the diversity of base summarizers with a general learning framework.  ...  We would like to thank Professor Jian-Yun Nie for helpful discussions and invaluable suggestions. Finally, We would like to thank the anonymous reviewers for their insightful comments.  ... 
doi:10.1145/1458082.1458201 dblp:conf/cikm/ZhangCWX08 fatcat:udayw3y5pfewnllik5mmbnjnd4

WSL-DS: Weakly Supervised Learning with Distant Supervision for Query Focused Multi-Document Abstractive Summarization [article]

Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang
2020 arXiv   pre-print
In the Query Focused Multi-Document Summarization (QF-MDS) task, a set of documents and a query are given where the goal is to generate a summary from these documents based on the given query.  ...  To overcome this issue, in this paper, we propose a novel weakly supervised learning approach via utilizing distant supervision.  ...  We acknowledge Compute Canada for providing us the computing resources.  ... 
arXiv:2011.01421v1 fatcat:fth4hcqwonafpcdptgrp3kwm6e

A Novel Feature-based Bayesian Model for Query Focused Multi-document Summarization [article]

Jiwei Li, Sujian Li
2013 arXiv   pre-print
Both supervised learning methods and LDA based topic model have been successfully applied in the field of query focused multi-document summarization.  ...  In this paper, we propose a novel supervised approach that can incorporate rich sentence features into Bayesian topic models in a principled way, thus taking advantages of both topic model and feature  ...  approach based on revised supervised topic model for query-focused multi document summarization.  ... 
arXiv:1212.2006v2 fatcat:bx2y2rga3jg5vkhwmdqmsxzpxm

Re-ranking Summaries Based on Cross-Document Information Extraction [chapter]

Heng Ji, Juan Liu, Benoit Favre, Dan Gillick, Dilek Hakkani-Tur
2010 Lecture Notes in Computer Science  
This paper describes a novel approach of improving multi-document summarization based on cross-document information extraction (IE).  ...  We describe a method to automatically incorporate IE results into sentence ranking.  ...  Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on.  ... 
doi:10.1007/978-3-642-17187-1_42 fatcat:ccwrcmavtvf2tfpc255pl47uvq

Modern Multi-Document Text Summarization Techniques

2020 International journal of recent technology and engineering  
In this paper, a thorough comparison of the several multi-document text summarization techniques such as Machine Learning based, Graph based, Game-Theory based and more has been presented.  ...  With the aid of this paper, researchers can identify the areas that present some scope for improvement and thereafter come up with novel or possibly hybrid techniques in Multi-Document Summarization.  ...  Multi Document summarization across various languages has been just as interesting of a topic for researchers [17] .  ... 
doi:10.35940/ijrte.a1945.059120 fatcat:evc3i323wjhlxkavul3clysaha

Extractive Multi-Document Text Summarization by Using Binary Particle Swarm Optimization

Archana Potnurwar
2020 Bioscience Biotechnology Research Communications  
The absence of a standard dataset and poor work for Hindi text summarization leads to develop a technique for better results.  ...  We have used a combination of Title feature, Sentence length, Sentence position, Numerical Data, Thematic word, Term frequency and Inverse Sentence Frequency for finding the results.  ...  This section aims to present an overview of the basics and types of multi-documents text summarization. x Wan proposed a novel extractive approach based on the manifold ranking for topic-focused multi-document  ... 
doi:10.21786/bbrc/13.14/8 fatcat:i5joc4qyxjd6lfi7plmobp42n4
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