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Clique-based clustering for improving named entity recognition systems

Julien Ah-Pine, Guillaume Jacquet
2009 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics on - EACL '09   unpublished
This system is based on a distributional approach which uses syntactic dependencies for measuring similarities between named entities.  ...  The specificity of the presented method however, is to combine a clique-based approach and a clustering technique that amounts to a soft clustering method.  ...  Named entity recognition (NER) is not a new domain (see MUC 1 and ACE 2 conferences) but some new needs appeared concerning NEs processing.  ... 
doi:10.3115/1609067.1609072 fatcat:qajujyta5zez3dol6zzipzcxu4

Wordnet-Based Criminal Networks Mining for Cybercrime Investigation

Farkhund Iqbal, Benjamin C. M. Fung, Mourad Debbabi, Rabia Batool, Andrew Marrington
2019 IEEE Access  
for crime investigation.  ...  In this paper, we propose a framework to analyze chat logs for crime investigation using data mining and natural language processing techniques.  ...  Mirza Ahmed for his contributions in the early stage of the project.  ... 
doi:10.1109/access.2019.2891694 fatcat:rebkgniucndvrcvyqbtip34jsa

Recognizing clinical entities in hospital discharge summaries using Structural Support Vector Machines with word representation features

Buzhou Tang, Hongxin Cao, Yonghui Wu, Min Jiang, Hua Xu
2013 BMC Medical Informatics and Decision Making  
systems for clinical entity recognition, when same features were used.  ...  Named entity recognition (NER) is an important task in clinical natural language processing (NLP) research.  ...  This work is based on an earlier work: "Clinical entity recognition using structural support vector machines with rich features", in  ... 
doi:10.1186/1472-6947-13-s1-s1 pmid:23566040 pmcid:PMC3618243 fatcat:ho332vbulbai7jcx7jgnzgt5g4

BIOKDD 2005 workshop report

Srinivasan Parthasarathy, Wei Wang, Mohammed Zaki
2005 SIGKDD Explorations  
the best algorithms for biomedical named-entity recognition and those for general newswire named-entity recognition.  ...  recognition algorithms that combine recognition results of various recognition systems.  ... 
doi:10.1145/1117454.1117472 fatcat:6mbi5aabrneslek5seugdpipey

A conditional random field approach for face identification in broadcast news using overlaid text

Gay Paul, Khoury Elie, Meignier Sylvain, Odobez Jean-Marc, Deleglise Paul
2014 2014 IEEE International Conference on Image Processing (ICIP)  
feature; a second CRF for the joint identification of the person clusters that improves identification performance thanks to the use of further diarization statistics.  ...  We investigate the problem of face identification in broadcast programs where people names are obtained from text overlays automatically processed with Optical Character Recognition (OCR) and further linked  ...  Face recognition in open sets is a difficult problem, but name entity detection from ASR could provide hypothesis on the faces likely to appear.  ... 
doi:10.1109/icip.2014.7025063 dblp:conf/icip/GayKMOD14 fatcat:7vkqdfq27reapnaca63h3noqo4

SoftNER: Mining Knowledge Graphs From Cloud Incidents [article]

Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan
2021 arXiv   pre-print
First, we build a novel multi-task learning based BiLSTM-CRF model which leverages not just the semantic context but also the data-types for extracting factual information in the form of named entities  ...  Next, we present an approach to mine relations between the named entities for automatically constructing knowledge graphs.  ...  learning based deep learning model for named-entity recognition which leverages not just the semantic features but also the data-types.  ... 
arXiv:2101.05961v2 fatcat:envypijvyvej3lieo3yqudf6ri

Neural Networks for Open Domain Targeted Sentiment

Meishan Zhang, Yue Zhang, Duy Tin Vo
2015 Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing  
We empirically study the effect of word embeddings and automatic feature combinations on the task by extending a CRF baseline using neural networks, which have demonstrated large potentials for sentiment  ...  Acknowledgments We thank the anonymous reviewers for their constructive comments, which helped to improve the paper.  ...  For scenario (2), a named entity recognition (NER) system can be used to extract targets, before the same targeted sentiment classification algorithms are applied.  ... 
doi:10.18653/v1/d15-1073 dblp:conf/emnlp/ZhangZV15 fatcat:zc345lma6vgg7izb3zlqbbeiou

Collective annotation of Wikipedia entities in web text

Sayali Kulkarni, Amit Singh, Ganesh Ramakrishnan, Soumen Chakrabarti
2009 Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '09  
We investigate practical solutions based on local hill-climbing, rounding integer linear programs, and pre-clustering entities followed by local optimization within clusters.  ...  Several systems have been proposed to link spots on Web pages to entities in Wikipedia.  ...  These entity ID annotations enable powerful join operations that can combine information across pages and sites. Named entity recognition and tagging have seen widespread success [17] .  ... 
doi:10.1145/1557019.1557073 dblp:conf/kdd/KulkarniSRC09 fatcat:hidofy3xnrgzxcxgbsymbdj7we

Concept Interpretation by Semantic Knowledge Harvesting

Jeena Sara Viju
2018 International Journal for Research in Applied Science and Engineering Technology  
A community blog is implemented in which the registered users in the community can text and the concept of the short text makes it possible to cluster the users.  ...  The main goal of the paper is to explore the semantics from short text and utilize it for proper decision making.  ...  An Efficient Trie-Based Method For Approximate Entity Extraction With Edit Distance Constraints Entity extraction (also known as entity recognition and entity identification) is an important operation  ... 
doi:10.22214/ijraset.2018.5081 fatcat:7dfs6w42yvgfhdwlclupe5gesu

Security techniques for intelligent spam sensing and anomaly detection in online social platforms

Monther Aldwairi, Loai Tawalbeh
2020 International Journal of Electrical and Computer Engineering (IJECE)  
This research provides a comprehensive related work survey and investigates the application of artificial neural networks for intrusion detection systems and spam filtering for OSNs.  ...  In addition, we use the concept of social graphs and weighted cliques in the detection of suspicious behavior of certain online groups and to prevent further planned actions such as cyber/terrorist attacks  ...  ACKNOWLEDGEMENTS This work was supported by Zayed University Research Office, Research Cluster Award #17079.  ... 
doi:10.11591/ijece.v10i1.pp275-287 fatcat:hucpuhkbhfam5efmyjva3l2iki

Named Entity Recognition with Bilingual Constraints

Wanxiang Che, Mengqiu Wang, Christopher D. Manning, Ting Liu
2013 North American Chapter of the Association for Computational Linguistics  
Different languages contain complementary cues about entities, which can be used to improve Named Entity Recognition (NER) systems.  ...  Bilingual NER experiments on the large OntoNotes 4.0 Chinese-English corpus show that the proposed method can improve strong baselines for both Chinese and English.  ...  Acknowledgments The authors would like to thank Rob Voigt and the three anonymous reviewers for their valuable comments and suggestions.  ... 
dblp:conf/naacl/CheWML13 fatcat:xgewk4kkajhdjhotuxe7n2iguu

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization

Hong-Jie Dai, Po-Ting Lai, Yung-Chun Chang, Richard Tsai
2015 Journal of Cheminformatics  
establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods.  ...  The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition  ...  Acknowledgements The authors would like to appreciate Johnny Chi-Yang Wu and Ted Knoy for their editorial assistances. Declarations  ... 
doi:10.1186/1758-2946-7-s1-s14 pmid:25810771 pmcid:PMC4331690 fatcat:n6ehsbyqk5fcningh47hs6m3zi

A History and Theory of Textual Event Detection and Recognition

Yanping Chen, Zehua Ding, Qinghua Zheng, Yongbin Qin, Ruizhang Huang, Nazaraf Shah
2020 IEEE Access  
Another important issue for named entity recognition is the nestification problem, where two named entities may overlap mutually.  ...  Based on VSM, various techniques are developed to improve system performance, e.g., techniques to improve clustering or evaluation, techniques to link the dependence among events and techniques to fuse  ... 
doi:10.1109/access.2020.3034907 fatcat:ng7mbplve5dttao7ro6e2623ti

Storytelling in entity networks to support intelligence analysts

M. Shahriar Hossain, Patrick Butler, Arnold P. Boedihardjo, Naren Ramakrishnan
2012 Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12  
We present a system to automatically construct stories in entity networks that can help form directed chains of relationships, with support for co-referencing, evidence marshaling, and imposing syntactic  ...  Intelligence analysts grapple with many challenges, chief among them is the need for software support in storytelling, i.e., automatically 'connecting the dots' between disparate entities (e.g., people  ...  [15] , graph-based analytic tools [16] [17] [18] [19] , and collaborative systems [5, 20, 21] .  ... 
doi:10.1145/2339530.2339742 dblp:conf/kdd/HossainBBR12 fatcat:lid22vjczjb4jgsie7gmzzsxja

Higher-Order Conditional Random Fields-Based 3D Semantic Labeling of Airborne Laser-Scanning Point Clouds

Yong Li, Dong Chen, Xiance Du, Shaobo Xia, Yuliang Wang, Sheng Xu, Qiang Yang
2019 Remote Sensing  
by turning the problem of topology maintenance into a clustering problem based on the proposed probability density clustering algorithm.  ...  In the hierarchical clustering, the raw point clouds are over-segmented into a set of fine-grained clusters by integrating the point density clustering and the classic K-means clustering algorithm, followed  ...  Acknowledgments: The authors would like to thank Zhenxin Zhang for providing the Tianjin data set for comparisons. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs11101248 fatcat:65amtljfujgelehc7gbgjnuaeu
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