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Time-aware Multi-Viewpoint Summarization of Multilingual Social Text Streams
2016
Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16
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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
2021
International Journal of Advanced Computer Science and Applications
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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
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)
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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
2012
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining - WISDOM '12
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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]
2019
arXiv
pre-print
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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]
2021
arXiv
pre-print
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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
2008
Proceeding of the 17th international conference on World Wide Web - WWW '08
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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]
2021
arXiv
pre-print
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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
2018
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
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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]
2008
arXiv
pre-print
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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]
2019
arXiv
pre-print
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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
2019
Proceedings of the ICA
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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
2020
Geosciences
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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
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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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
2022
ACM Computing Surveys
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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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