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Chinese Semantic Role Labeling with Dependency-Driven Constituent Parse Tree Structure [chapter]

Hongling Wang, Bukang Wang, Guodong Zhou
2012 Communications in Computer and Information Science  
In particular, a new dependency-driven constituent parse tree (D-CPT) structure is proposed to better represent the dependency relations in a CPT-style structure, which employs dependency relation types  ...  This indicates the effectiveness of the novel D-CPT structure for better representation of dependency relations in tree kernel-based methods.  ...  , extracted from the DPT structure, to a similar task of semantic relation extraction between named entities.  ... 
doi:10.1007/978-3-642-34456-5_10 fatcat:bwalojkyl5eknnequ46t2vpsd4

Extracting Deep Personae Social Relations in Microblog Posts

Ya Jun Du, Fang Hong Su, An Zheng Yang, Xian Yong Li, Yong Quan Fan
2019 IEEE Access  
To deeply extract the personal social relationships of microblog posts, we define the relation feature words, provide seven rules for extracting these feature words, and propose a rule-based approach that  ...  In this paper, we improve a novel kernel-based learning algorithm to mine the personae social relationships from microblog posts by combining the syntax and semantic meanings of the dependency trigram  ...  [26] proposed a convolution tree kernel-based method to extract Chinese semantic relations.  ... 
doi:10.1109/access.2019.2960659 fatcat:uib5ydcrmvao7k7lfqom7xzwdq

Relation Extraction : A Survey [article]

Sachin Pawar, Girish K. Palshikar, Pushpak Bhattacharyya
2017 arXiv   pre-print
Occurrences of entities in a sentence are often linked through well-defined relations; e.g., occurrences of person and organization in a sentence may be linked through relations such as employed at.  ...  The task of Relation Extraction (RE) is to identify such relations automatically. In this paper, we survey several important supervised, semi-supervised and unsupervised RE techniques.  ...  Acknowledgement The authors would like to thank Swapnil Hingmire for his efforts of reviewing the draft and providing several useful suggestions for improvement.  ... 
arXiv:1712.05191v1 fatcat:aiezdqep3faltozs6gusvxoite

Automatic Expansion of DBpedia Exploiting Wikipedia Cross-Language Information [chapter]

Alessio Palmero Aprosio, Claudio Giuliano, Alberto Lavelli
2013 Lecture Notes in Computer Science  
We evaluated our system using a manually annotated test set, demonstrating that our approach can add more than 1M new entities to DBpedia with high precision (90%) and recall (50%).  ...  DBpedia is a project aiming to represent Wikipedia content in RDF triples. It plays a central role in the Semantic Web, due to the large and growing number of resources linked to it.  ...  This can be seen as a relation extraction task, and one of the most reliable approaches to tackle this problem (starting from a large available knowledge base) is distant supervision [14] .  ... 
doi:10.1007/978-3-642-38288-8_27 fatcat:wxwgyn7htngjjibukpkuront4u

Do We Really Need All Those Rich Linguistic Features? A Neural Network-Based Approach to Implicit Sense Labeling

Niko Schenk, Christian Chiarcos, Kathrin Donandt, Samuel Rönnqvist, Evgeny Stepanov, Giuseppe Riccardi
2016 Proceedings of the CoNLL-16 shared task  
We describe our contribution to the CoNLL 2016 Shared Task on shallow discourse parsing. 1 Our system extends the two best parsers from previous year's competition by integration of a novel implicit sense  ...  It is grounded on a highly generic, language-independent feedforward neural network architecture incorporating weighted word embeddings for argument spans which obviates the need for (traditional) hand-crafted  ...  ., 2014) and propose a novel, neural network-based approach for implicit sense labeling.  ... 
doi:10.18653/v1/k16-2005 dblp:conf/conll/SchenkCDRSR16 fatcat:hzcf2f2rjzgvnkcmjidulq6mhe

Big Data and Network Biology

Shigehiko Kanaya, Md. Altaf-Ul-Amin, Samuel Kuria Kiboi, Farit Mochamad Afendi
2014 BioMed Research International  
The paper entitled "A knowledge-driven approach to extract disease-related biomarkers from the literature" developed a text mining approach to extract a dataset of biomarkers related to diseases covering  ...  The paper entitled "A novel feature selection strategy for enhanced biomedical event extraction using the Turku system" proposed a method to enhance the performance of Turku Event Extraction System (TEES  ...  The paper entitled "A knowledge-driven approach to extract disease-related biomarkers from the literature" developed a text mining approach to extract a dataset of biomarkers related to diseases covering  ... 
doi:10.1155/2014/836708 pmid:25025069 pmcid:PMC4082900 fatcat:zwa7a4r4bbfaxgz2c6wgsa6zde

Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks

Huaiyu Wan, Marie-Francine Moens, Walter Luyten, Xuezhong Zhou, Qiaozhu Mei, Lu Liu, Jie Tang
2015 JAMIA Journal of the American Medical Informatics Association  
Results We perform our method to extract relations from a large dataset consisting of more than 100,000 abstracts of TCM papers.  ...  We first construct heterogeneous entity networks from the TCM literature, in which each edge is a candidate relation, and then present a heterogeneous factor graph model (HFGM) to simultaneously infer  ...  The main contribution in this paper is proposing a novel relation extraction approach to collectively and globally extract relations from the entire TCM corpus, from the perspective of 5 network mining  ... 
doi:10.1093/jamia/ocv092 pmid:26224335 fatcat:dtsolyxzwrghpdf63qve3bzi74

Information Extraction from the Text Data on Traditional Chinese Medicine: A Review on Tasks, Challenges, and Methods from 2010 to 2021

Tingting Zhang, Zonghai Huang, Yaqiang Wang, Chuanbiao Wen, Yangzhi Peng, Ying Ye, Xuezhong Zhou
2022 Evidence-Based Complementary and Alternative Medicine  
In the future, IE work should be promoted by extracting more existing entities and relations, constructing gold standard data sets, and exploring IE methods based on a small amount of labeled data.  ...  Developing a method of information extraction (IE) from these sources to generate a cohesive data set would be a great contribution to the medical field.  ...  www.internationalscienceediting.com) for editing this manuscript. is work was supported by the National Natural Science Foundation of China (Grant no. 61801058) and Talent Fund of Chengdu University of Traditional Chinese  ... 
doi:10.1155/2022/1679589 pmid:35600940 pmcid:PMC9122692 fatcat:r7sj7sdoubhwfhcscj227neoiy

Using a Hybrid Convolution Tree Kernel for Semantic Role Labeling

Wanxiang Che, Min Zhang, AiTi Aw, ChewLim Tan, Ting Liu, Sheng Li
2008 ACM Transactions on Asian Language Information Processing  
In this article, a hybrid convolution tree kernel is proposed to model different linguistic objects. The hybrid convolution tree kernel consists of two individual convolution tree kernels.  ...  As an extension of feature-based methods, kernel-based methods are able to capture structured features more efficiently in a much higher dimension.  ...  Moreover, we can also explore the hybrid convolution tree kernel method in other tasks, such as relation extraction in the future.  ... 
doi:10.1145/1450295.1450298 fatcat:2rz7iurirrgizk2ug7cgs57e4i

Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval [article]

Zhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan Liu
2018 arXiv   pre-print
The two components are learned end-to-end, making EDRM a natural combination of entity-oriented search and neural information retrieval.  ...  This paper presents the Entity-Duet Neural Ranking Model (EDRM), which introduces knowledge graphs to neural search systems.  ...  We thank Sogou for providing access to the search log.  ... 
arXiv:1805.07591v2 fatcat:ns3hh65qhbbmvfmku6nm4ky6d4

Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval

Zhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan Liu
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
This paper presents the Entity-Duet Neural Ranking Model (EDRM), which introduces knowledge graphs to neural search systems.  ...  The two components are learned end-to-end, making EDRM a natural combination of entityoriented search and neural information retrieval.  ...  We thank Sogou for providing access to the search log.  ... 
doi:10.18653/v1/p18-1223 dblp:conf/acl/SunLXL18 fatcat:uoal5wyyzvhylgahyrnisfltpi

Enhancing Multi-lingual Information Extraction via Cross-Media Inference and Fusion

Adam Lee, Marissa Passantino, Heng Ji, Guojun Qi, Thomas S. Huang
2010 International Conference on Computational Linguistics  
We describe a new information fusion approach to integrate facts extracted from cross-media objects (videos and texts) into a coherent common representation including multi-level knowledge (concepts, relations  ...  We further extended our methods to multi-lingual environment (English, Arabic and Chinese) by presenting a case study on cross-lingual comparable corpora acquisition based on video comparison.  ...  Saggion et al. (2004) described a multimedia extraction approach to create composite index from multiple and multi-lingual sources.  ... 
dblp:conf/coling/LeePJQH10 fatcat:xcvpn4dsp5c7rj2qhrys7mmpm4

A Joint Model of Entity Linking and Predicate Recognition for Knowledge Base Question Answering

Yang Li, Qingliang Miao, ChenXin Yin, Chao Huo, Wenxiang Mao, Changjian Hu, Feiyu Xu
2018 China Conference on Knowledge Graph and Semantic Computing  
Second, we use a joint training entity linking and predicate recognition model to re-rank candidate triple paths for the question.  ...  In the paper, we build a QA system which can automatically find the right answers from Chinese knowledge base.  ...  Lai [4] proposed a novel method based on deep CNNs to rerank the entity-predicate pairs which generated by shallow features.  ... 
dblp:conf/ccks/LiMYHMHX18 fatcat:qia6vzjiqzg2rh6md7zfhl5i6a

Message from the general chair

Benjamin C. Lee
2015 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)  
To maximize the utility of the injected knowledge, we deploy a learning-based multi-sieve approach and develop novel entity-based features.  ...  To inject knowledge, we use a state-of-the-art system which cross-links (or "grounds") expressions in free text to Wikipedia.  ...  This paper proposes a methodological approach to temporally anchored relation extraction.  ... 
doi:10.1109/ispass.2015.7095776 dblp:conf/ispass/Lee15 fatcat:ehbed6nl6barfgs6pzwcvwxria

Open Domain Chinese Triples Hierarchical Extraction Method

Chunhui He, Zhen Tan, Haoran Wang, Chong Zhang, Yanli Hu, Bin Ge
2020 Applied Sciences  
text to expand entities and relations.  ...  This method can recognize the named entities from Chinese sentences to establish entity pairs, and implement hierarchical extraction of specific and open relations based on the user-defined schema library  ...  Some studies have used these approaches to complete relation classification [25] [26] [27] and have achieved a higher accuracy.  ... 
doi:10.3390/app10144819 fatcat:2mlm2zys4bftpghnu7l47d5r6i
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