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Text summarization in the biomedical domain: A systematic review of recent research

Rashmi Mishra, Jiantao Bian, Marcelo Fiszman, Charlene R. Weir, Siddhartha Jonnalagadda, Javed Mostafa, Guilherme Del Fiol
2014 Journal of Biomedical Informatics  
Most studies (28; 82%) conducted an intrinsic evaluation. Discussion: This is the first systematic review of text summarization in the biomedical domain.  ...  Investigators independently screened and abstracted studies that examined text summarization techniques in the biomedical domain.  ...  This project was supported by Grant Number 1R01LM011416-01 from the National Library of Medicine. Appendix A.  ... 
doi:10.1016/j.jbi.2014.06.009 pmid:25016293 pmcid:PMC4261035 fatcat:jdsabkdlhneldlzelmbdqp3bci

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.  ...  The Benchmark datasets of this domain and their features have also been examined.  ...  Introduction Cross-Language Text Summarization (CLTS) is about studying a record in a language input to get its features and produce a small, informative and accurate summary of this content in a target  ... 
doi:10.35940/ijrte.a1945.059120 fatcat:evc3i323wjhlxkavul3clysaha

Video Summarization: Survey

Suraj Fule
2019 International Journal for Research in Applied Science and Engineering Technology  
Sound information in videos plays an important role in shaping the user feelings and experience. When sound is not available in videos, text captions are used to provide sound information.  ...  Sound is one of human beings most important senses. After vision it is the sense most used to gather the information about the environment.  ...  APPLICATIONS Video Summarization. Statistical Feature Extraction Data Based Syntactical Feature Extraction Data with structure Semantic Feature Extraction Prior knowledge of Environment VI.  ... 
doi:10.22214/ijraset.2019.5404 fatcat:rxjl4wfjlbdg3kr4n7bqc2x6cm

Content-enriched classifier for web video classification

Bin Cui, Ce Zhang, Gao Cong
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
In this paper we propose a novel video classification framework that is able to exploit both content and text features for video classification while avoiding the expensive computation of extracting content  ...  The content-enriched semantic kernels enable to utilize both content and text features for classifying new videos without extracting their content features.  ...  First, our framework is comparable to the text-based framework in Figure 1 (a) in terms of classification efficiency.  ... 
doi:10.1145/1835449.1835553 dblp:conf/sigir/CuiZC10 fatcat:ol573uak7fc37go5kfcjlgj6se

A Corpus-Driven Analysis of Collocational Framework the * of in the Legal Text: A Case Study of The Criminal Law of the PRC

Bao-Xia XIE, Jun-Cheng CHEN
2019 DEStech Transactions on Social Science Education and Human Science  
the features and functions of the collocational framework the * of in the legal text.  ...  Collocational framework is a critical part of the studies of phraseology.  ...  Generally, few studies have been conducted on the form and function of collocational framework in the legal text.  ... 
doi:10.12783/dtssehs/icesd2019/28075 fatcat:rjoasl5ghze4haax44hprhpgjq

The role of statistical and semantic features in single-document extractive summarization

Tatiana Vodolazova
2013 Artificial intelligence research  
This paper reports on the further results of the ongoing research analyzing the impact of a range of commonly used statistical and semantic features in the context of extractive text summarization.  ...  The obtained results demonstrate the relative importance of each feature and the limitations of the tools available.  ...  Conclusions and future work The goal of the present research is to study the interaction between a set of statistical and semantic features and their impact on the process of extractive text summarization  ... 
doi:10.5430/air.v2n3p35 fatcat:7nfvz43w6rautlsvwiq56lqgmu

Evaluation of Content Compaction in Assamese Language

Nomi Baruah, Shikhar Kr. Sarma, Surajit Borkotokey
2020 Procedia Computer Science  
This paper proposes a content compaction approach for Assamese Text to generate a summary by incorporating statistical and linguistic features and makes an attempt to extract the relevant points in the  ...  This paper proposes a content compaction approach for Assamese Text to generate a summary by incorporating statistical and linguistic features and makes an attempt to extract the relevant points in the  ...  A few text summarization approaches in Indian languages consisting of linguistic and statistical features are stated as follows: Numerical-Based Approach Numerical scores are assigned to text elements  ... 
doi:10.1016/j.procs.2020.04.246 fatcat:vq42hmtllve4di6jgw7dkuww2y

Semantically linking molecular entities in literature through entity relationships

Sofie Van Landeghem, Jari Björne, Thomas Abeel, Bernard De Baets, Tapio Salakoski, Yves Van de Peer
2012 BMC Bioinformatics  
Results: We describe, compare and evaluate two frameworks developed for the prediction of non-causal or 'entity' relations (REL) between gene symbols and domain terms.  ...  It is crucial that such tools extract information with a sufficient level of detail to be applicable in real life scenarios.  ...  The authors would like to thank the Shared Task organizers for providing the dataset and evaluation framework for this task.  ... 
doi:10.1186/1471-2105-13-s11-s6 pmid:22759460 pmcid:PMC3384255 fatcat:jih7cgrb2zgjlggvskbnyruxue

Covid-Transformer: Detecting COVID-19 Trending Topics on Twitter Using Universal Sentence Encoder [article]

Meysam Asgari-Chenaghlu, Narjes Nikzad-Khasmakhi, Shervin Minaee
2020 arXiv   pre-print
After that, the cluster summary is obtained using a text summarization algorithm based on deep learning, which can uncover the underlying topics of each cluster.  ...  We used universal sentence encoder in order to derive the semantic representation and the similarity of tweets.  ...  Conclusion In this work, we proposed a trending topic detection framework using a method that combines the Transformers with text summarization in a smart way, and applied that to COVID-19 related Tweets  ... 
arXiv:2009.03947v3 fatcat:vcsrfx7x2jcipgcej2ylsfzj3a

Topic-Guided Abstractive Text Summarization: a Joint Learning Approach [article]

Chujie Zheng, Kunpeng Zhang, Harry Jiannan Wang, Ling Fan, Zhe Wang
2021 arXiv   pre-print
We introduce a new approach for abstractive text summarization, Topic-Guided Abstractive Summarization, which calibrates long-range dependencies from topic-level features with globally salient content.  ...  The idea is to incorporate neural topic modeling with a Transformer-based sequence-to-sequence (seq2seq) model in a joint learning framework.  ...  This framework has extended the success of text generation to summarization and achieved many promising results.  ... 
arXiv:2010.10323v2 fatcat:bapqwlrdsjbvro4sgbbh77qbpe

Special Issue Editorial: Cognitively-Inspired Computing for Knowledge Discovery

Kaizhu Huang, Rui Zhang, Xiaobo Jin, Amir Hussain
2018 Cognitive Computation  
A number of successful models have recently emerged and led to great impact in the field.  ...  On the other hand, it is also crucially challenging to extract, summarize, and even generate knowledge due to the large-scale, noisy, heterogeneous nature of big data.  ...  A number of successful models have recently emerged and led to great impact in the field.  ... 
doi:10.1007/s12559-017-9532-y fatcat:64jcrljij5d6xgqjemgijftp7m

Exploiting internal and external semantics for the clustering of short texts using world knowledge

Xia Hu, Nan Sun, Chao Zhang, Tat-Seng Chua
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
In this paper, we propose a novel framework to improve the performance of short text clustering by exploiting the internal semantics from the original text and external concepts from world knowledge.  ...  The proposed method employs a hierarchical three-level structure to tackle the data sparsity problem of original short texts and reconstruct the corresponding feature space with the integration of multiple  ...  In this paper, we present a novel framework to improve the clustering of short texts by incorporating both the rich internal and external semantics.  ... 
doi:10.1145/1645953.1646071 dblp:conf/cikm/HuSZC09 fatcat:je6zmajetbbg7or72m2poajlcu

Summarizing large text collection using topic modeling and clustering based on MapReduce framework

N K Nagwani
2015 Journal of Big Data  
Summarizing large volume of text is a challenging and time consuming problem particularly while considering the semantic similarity computation in summarization process.  ...  The advantages of MapReduce framework are clearly visible from the experiments and it is also demonstrated that MapReduce provides a faster implementation of summarizing large text collections and is a  ...  Acknowledgments The authors want to thank National Institute of Technology Raipur, India for providing infrastructure and facilities to carry out this research work.  ... 
doi:10.1186/s40537-015-0020-5 fatcat:r5uojaicofamvpqhlo4vzvgvna

Turkish Natural Language Processing Studies

E Yilmaz Ince
2019 Zenodo  
Evaluated in terms of the subjects of the study samples obtained as a result of the literature review Morphological analysis studies, syntactic analysis studies, semantic analysis studies and problem analysis  ...  Documentation on the current method of examination to be reliable scientific research and thesis studies on natural language processing in Turkey were examined by scanning pages of the thesis of Higher  ...  Numerous keyword extraction and text summarization algorithms in the field of natural language processing, some of which we discussed in the study (Güvenç, 2016) .  ... 
doi:10.5281/zenodo.3610009 fatcat:5ivzxoqnn5blpgczh43yw4hyeu

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports

Xiao Liu, Hsinchun Chen
2015 Journal of Biomedical Informatics  
In this study, we develop a research framework with advanced natural language processing techniques for integrated and highperformance patient reported adverse drug event extraction.  ...  To evaluate the proposed framework, a series of experiments were conducted on a test bed encompassing about postings from major diabetes and heart disease forums in the United States.  ...  We gratefully acknowledge the contribution of Dr. Randall Brown and Ms. Chanadda Chinthammit for their advices from clinical and pharmaceutical perspectives in this study.  ... 
doi:10.1016/j.jbi.2015.10.011 pmid:26518315 fatcat:53nu3jrxfbdmxe2yqpaaqyrija
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