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Time-aware Multi-Viewpoint Summarization of Multilingual Social Text Streams

Zhaochun Ren, Oana Inel, Lora Aroyo, Maarten de Rijke
2016 Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16  
Time-aware multi-viewpoint summarization of multilingual social text streams Ren, Z.; Inel, O.; Aroyo, L.; de Rijke, M.  ...  We use the Topic-aspect model [36, TAM] and the Sentiment-topic model [28, as baselines for topic models.  ...  After cross-language viewpoint alignment, we apply a random walk ranking strategy to extract documents to tackle the time-aware multi-viewpoint summarization problem.  ... 
doi:10.1145/2983323.2983710 dblp:conf/cikm/RenIAR16 fatcat:f34xytwsibaqvb2p3tdyi5l2xe

Knowledge Base Driven Automatic Text Summarization using Multi-objective Optimization

Chihoon Jung, Wan Chul Yoon, Rituparna Datta, Sukhwan Jung
2021 International Journal of Advanced Computer Science and Applications  
Next, an improvement on the multi-objective optimization algorithm is also proposed for the automatic text summarization problem.  ...  The experiments on DUC2002 and DUC2004 multi-document summarization task dataset shows that the proposed model is effective compared to other methods.  ...  Each of these summarization types has an alternative approach, namely, query-focused, abstractive, and single-document summarization.  ... 
doi:10.14569/ijacsa.2021.0120895 fatcat:dhx6it637nahzp2r5jp3a2dk44

Subtopic-driven Multi-Document Summarization

Xin Zheng, Aixin Sun, Jing Li, Karthik Muthuswamy
2019 Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)  
In multi-document summarization, a set of documents to be summarized is assumed to be on the same topic, known as the underlying topic in this paper.  ...  In this paper, we propose a summarization model called STDS. The model generates the underlying topic representation from both document view and subtopic view in parallel.  ...  AAPRW (Wang et al., 2017) : This is an adjustable affinity-preserving random walk model to keep the summary diverse.  ... 
doi:10.18653/v1/d19-1311 dblp:conf/emnlp/ZhengSLM19 fatcat:urwhgj2qkrblpmu4mmqxax5zbu

A unified graph model for Chinese product review summarization using richer information

He Huang, Chunping Li
2012 Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining - WISDOM '12  
Based on the model, we propose an automatic approach to address this issue.  ...  Experimental results show that the proposed approach helps to build an effective way towards both the overall and contrastive summarization.  ...  He performed a Markov Random Walk in an aspect-sentiment graph to generate summaries. Some other scholars also focused on contradiction detection.  ... 
doi:10.1145/2346676.2346678 fatcat:6v6xy2jhiffwhm6lgks4tcotju

Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization [article]

Diego Antognini, Boi Faltings
2019 arXiv   pre-print
To our knowledge, we are the first to use multiple sentence embeddings for the task of multi-document summarization.  ...  Linking facts across documents is a challenging task, as the language used to express the same information in a sentence can vary significantly, which complicates the task of multi-document summarization  ...  Acknowledgments We thank Michaela Benk for proofreading and helpful advice.  ... 
arXiv:1909.12231v1 fatcat:juuj6yelfnhg3mqd76gemresym

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization [article]

Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev
2021 arXiv   pre-print
In order to satisfy the needs of different types of users, we define a new query-based multi-domain meeting summarization task, where models have to select and summarize relevant spans of meetings in response  ...  Experimental results and manual analysis reveal that QMSum presents significant challenges in long meeting summarization for future research. Dataset is available at .  ...  We would also like to thank annotators for their hard work and reviewers for their valuable comments. The Usage of Tense. Since all the meetings happened, we ask annotators to use past tense.  ... 
arXiv:2104.05938v1 fatcat:24p3u2nimrei7mwnwr32ouk2qq

Modeling online reviews with multi-grain topic models

Ivan Titov, Ryan McDonald
2008 Proceeding of the 17th international conference on World Wide Web - WWW '08  
Our models are based on extensions to standard topic modeling methods such as LDA and PLSA to induce multi-grain topics.  ...  The models we present not only extract ratable aspects, but also cluster them into coherent topics, e.g., waitress and bartender are part of the same topic staff for restaurants.  ...  However, it is possible to construct a multi-grain model which uses a n-gram topic model for local topics and a distribution fixed per document for global topics.  ... 
doi:10.1145/1367497.1367513 dblp:conf/www/TitovM08 fatcat:jfdq3qbhnzbg7daujy265w2vri

AI in Finance: Challenges, Techniques and Opportunities [article]

Longbing Cao
2021 arXiv   pre-print
We then structure and illustrate the data-driven analytics and learning of financial businesses and data.  ...  The comparison, criticism and discussion of classic vs. modern AI techniques for finance are followed.  ...  Random methods Random sampling, random walk models, random forest, stochastic theory, fuzzy set theory, quantum mechanics, etc.  ... 
arXiv:2107.09051v1 fatcat:g62cz4dqt5dcrbckn4lbveat3u

Neural Related Work Summarization with a Joint Context-driven Attention Mechanism

Yongzhen Wang, Xiaozhong Liu, Zheng Gao
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Our motivation is to maintain the topic coherency between a related work section and its target document, where both the textual and graphic contexts play a big role in characterizing the relationship  ...  In this paper, we develop a neural data-driven summarizer by leveraging the seq2seq paradigm, in which a joint context-driven attention mechanism is proposed to measure the contextual relevance within  ...  Acknowledgement We would like to thank the anonymous reviewers for their valuable comments. This work is partially supported by the National Science Foundation of China under grant No. 71271034.  ... 
doi:10.18653/v1/d18-1204 dblp:conf/emnlp/WangLG18 fatcat:5u3y6mv7kjgddihhfdwvdxv2ra

Modeling Online Reviews with Multi-grain Topic Models [article]

Ivan Titov, Ryan McDonald
2008 arXiv   pre-print
Our models are based on extensions to standard topic modeling methods such as LDA and PLSA to induce multi-grain topics.  ...  We argue that multi-grain models are more appropriate for our task since standard models tend to produce topics that correspond to global properties of objects (e.g., the brand of a product type) rather  ...  As an application they consider prediction of the overall document sentiment, though they do not consider multi-aspect ranking.  ... 
arXiv:0801.1063v1 fatcat:byn2w64oszdevdl4vy6i76tsje

Neural Related Work Summarization with a Joint Context-driven Attention Mechanism [article]

Yongzhen Wang, Xiaozhong Liu, Zheng Gao
2019 arXiv   pre-print
Our motivation is to maintain the topic coherency between a related work section and its target document, where both the textual and graphic contexts play a big role in characterizing the relationship  ...  In this paper, we develop a neural data-driven summarizer by leveraging the seq2seq paradigm, in which a joint context-driven attention mechanism is proposed to measure the contextual relevance within  ...  Acknowledgement We would like to thank the anonymous reviewers for their valuable comments. This work is partially supported by the National Science Foundation of China under grant No. 71271034.  ... 
arXiv:1901.09492v1 fatcat:nwyplxa2u5gmpez3ic6wydfgne

Research on event perception based on geo-tagged social media data

Ruoxin Zhu, Chenyu Zuo, Diao Lin
2019 Proceedings of the ICA  
This paper provides an overview of event study based on geo-tagged social media data. Firstly, we introduce the event model and the characteristics of social media data.  ...  When a notable event occurs, social media serves a popular platform for citizens to share event-related information.  ...  (2017) proposed a three-stage framework for event detection. First, the multimodal fusion model combined soft-voting strategy and graph random walk model was used to obtain fused features.  ... 
doi:10.5194/ica-proc-2-157-2019 fatcat:i2vo6okebvfgjl5xuiid235a3m

Systematic Literature Review on Data-Driven Models for Predictive Maintenance of Railway Track: Implications in Geotechnical Engineering

Jiawei Xie, Jinsong Huang, Cheng Zeng, Shui-Hua Jiang, Nathan Podlich
2020 Geosciences  
Among these data-driven model applications, the collected data types are the most critical factors which affect selecting suitable models.  ...  This study presents a systematic literature review of data-driven models applied in the predictive maintenance of railway track.  ...  The word importance was explored by considering term frequency and inverse document frequency indices. Random forest and logistic regression methods were applied using these indices.  ... 
doi:10.3390/geosciences10110425 fatcat:r73zrv554vcsnjbi2aaeswvbsq

A Simple Theoretical Model of Importance for Summarization

Maxime Peyrard
2019 Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics  
We argue that establishing theoretical models of Importance will advance our understanding of the task and help to further improve summarization systems.  ...  Research on summarization has mainly been driven by empirical approaches, crafting systems to perform well on standard datasets with the notion of information Importance remaining latent.  ...  We also thank the anonymous reviewers for their comments.  ... 
doi:10.18653/v1/p19-1101 dblp:conf/acl/Peyrard19 fatcat:v75d4appkrchlf5fteqnmrz3o4

Survey on the Objectives of Recommender System: Measures, Solutions, Evaluation Methodology, and New Perspectives

Bushra Alhijawi, Arafat Awajan, Salam Fraihat
2022 ACM Computing Surveys  
Research in the recommender system field has traditionally focused on the accuracy of predictions and the relevance of recommendations.  ...  Recently, recommender systems have played an increasingly important role in a wide variety of commercial applications to help users find favourite products.  ...  Topic modeling is an unsupervised learning algorithm based on statistics for discovering abstract "topics" that emerge in a set of documents.  ... 
doi:10.1145/3527449 fatcat:xc4ibrglpjgqzlgttplmgitedu
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