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Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature

Arjun Magge, Davy Weissenbacher, Abeed Sarker, Matthew Scotch, Graciela Gonzalez-Hernandez
2018 Biocomputing 2019  
In this paper, we present an extensive study of multiple recurrent neural network architectures for the task of extracting geographic locations and their effective contribution to the disambiguation task  ...  using population heuristics.  ...  Acknowledgments AM designed and trained the neural networks, ran the experiments, performed the error analysis, and wrote most of the manuscript.  ... 
doi:10.1142/9789813279827_0010 fatcat:wikd6k67brfeje4ukexmy7amym

Bi-directional Recurrent Neural Network Models for Geographic Location Extraction in Biomedical Literature

Arjun Magge, Davy Weissenbacher, Abeed Sarker, Matthew Scotch, Graciela Gonzalez-Hernandez
2019 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
In this paper, we present an extensive study of multiple recurrent neural network architectures for the task of extracting geographic locations and their effective contribution to the disambiguation task  ...  using population heuristics.  ...  Acknowledgments AM designed and trained the neural networks, ran the experiments, performed the error analysis, and wrote most of the manuscript.  ... 
pmid:30864314 pmcid:PMC6417823 fatcat:helldhcubncu3c24y35cvqeieq

University of

Vikas Yadav, Egoitz Laparra, Ti-Tai Wang, Mihai Surdeanu, Steven Bethard
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
We used the unsupervised population heuristics for task 3 and achieved 52.99% strict micro-F1 score in this task.  ...  We implemented a deep-affix based LSTM-CRF NER model for task 1, which utilizes only character, word, prefix and suffix information for the identification of geolocation entities.  ...  In the P opulation heuristic, the system simply assigns the geonameID of the most populous 4 candidate for the current location.  ... 
doi:10.18653/v1/s19-2232 dblp:conf/semeval/YadavLWSB19 fatcat:p5azmxawbjerno6f3cj7gle5nq

Are We There Yet? Evaluating State-of-the-Art Neural Network based Geoparsers Using EUPEG as a Benchmarking Platform [article]

Jimin Wang, Yingjie Hu
2020 arXiv   pre-print
The winning teams developed neural network based geoparsers that achieved outstanding performances (over 90% precision, recall, and F1 score for toponym recognition).  ...  A geoparsing system, known as a geoparser, takes some texts as the input and outputs the recognized place mentions and their location coordinates.  ...  ACKNOWLEDGMENTS The authors would like to thank the four anonymous reviewers for their constructive comments and suggestions.  ... 
arXiv:2007.07455v1 fatcat:vtrnqpjn35ggllqqvivn7qkb5a

RGCL-WLV at SemEval-2019 Task 12: Toponym Detection

Alistair Plum, Tharindu Ranasinghe, Pablo Calleja, Constantin Orăsan, Ruslan Mitkov
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
The highest precision achieved for one of the submissions was 89%, albeit it at a relatively low recall of 49%.  ...  The system detects toponyms using a bootstrapped machine learning (ML) approach which classifies names identified using gazetteers extracted from the GeoNames geographical database.  ...  The first one contained all locations from the GeoNames geographical database. The second gazetteer contained a list of cities from GeoNames with a population of over 5,000.  ... 
doi:10.18653/v1/s19-2228 dblp:conf/semeval/PlumRCOM19 fatcat:kjwvhwrpdjdsvcipy6ruolsloa

Which Melbourne? Augmenting Geocoding with Maps

Milan Gritta, Mohammad Taher Pilehvar, Nigel Collier
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
We introduce a geocoder (location mention disambiguator) that achieves state-of-the-art (SOTA) results on three diverse datasets by exploiting the implicit lexical clues.  ...  To that end, we introduce the Map Vector (MapVec), a sparse representation obtained by plotting prior geographic probabilities, derived from population figures, on a World Map.  ...  We also gratefully acknowledge NVIDIA Corporation's donation of the Titan Xp GPU used for this research.  ... 
doi:10.18653/v1/p18-1119 dblp:conf/acl/CollierPG18 fatcat:7gdu2tfz6naflheumxdtjkzozy

UNH at SemEval-2019 Task 12: Toponym Resolution in Scientific Papers

Matthew Magnusson, Laura Dietz
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
We propose two methods: 1) sliding window convolutional neural network using ELMo embeddings (CNN-ELMo), and 2) sliding window multi-Layer perceptron using ELMo embeddings (MLP-ELMo).  ...  We focus on Subtask 1: Toponym Detection which is the identification of spans of text for place names mentioned in a document.  ...  Gazeteer Features: a set of toponynm tokens is generated from the entries in GeoNames. 3 For example, for the entry in Geonames,"Gulf of Mexico", the tokens "Gulf", "of", and "Mexico" are added to the  ... 
doi:10.18653/v1/s19-2230 dblp:conf/semeval/MagnussonD19 fatcat:iu3i3k46ujgzxhw2c2gxcnhpaq

SemEval-2019 Task 12: Toponym Resolution in Scientific Papers

Davy Weissenbacher, Arjun Magge, Karen O'Connor, Matthew Scotch, Graciela Gonzalez-Hernandez
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
In Subtask 2, given toponym mentions as input, we asked participants to disambiguate them by linking them to entries in GeoNames.  ...  Given an article from PubMed, the task consists of detecting mentions of names of places, or toponyms, and mapping the mentions to their corresponding entries in GeoNames.org, a database of geospatial locations  ...  GeoNames 2 is a crowdsourced database of geospatial locations and freely available.  ... 
doi:10.18653/v1/s19-2155 dblp:conf/semeval/WeissenbacherMO19 fatcat:pkbj53fndnc3leh2peai4rwf5a

DM_NLP at SemEval-2018 Task 12: A Pipeline System for Toponym Resolution

Xiaobin Wang, Chunping Ma, Huafei Zheng, Chu Liu, Pengjun Xie, Linlin Li, Luo Si
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
For ranking, we proposed several effective features for measuring the consistency between the detected toponym and toponyms in GeoNames.  ...  This paper describes DM-NLP's system for toponym resolution task at Semeval 2019.  ...  Designing a neural network architecture with character representation as input is appealing for several reasons.  ... 
doi:10.18653/v1/s19-2156 dblp:conf/semeval/WangMZLXLS19 fatcat:v35fcolkzjh2fhic66i2pi7wia

THU_NGN at SemEval-2019 Task 12: Toponym Detection and Disambiguation on Scientific Papers

Tao Qi, Suyu Ge, Chuhan Wu, Yubo Chen, Yongfeng Huang
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
For toponym disambiguation, we propose a heuristics rule-based method using toponym frequency and population.  ...  For toponym detection, in our approach we use TagLM as the basic model, and explore the use of various features in this task, such as word embeddings extracted from pre-trained language models, POS tags  ...  In recent years, many neural network based methods have been proposed for NER. For example, Ma and Hovy (2016) proposed a CNN-LSTM-CRF model for NER.  ... 
doi:10.18653/v1/s19-2229 dblp:conf/semeval/QiGW0H19 fatcat:ummmz5gaonbmvm7ovfk7cjr25m

Deep Learning for Toponym Resolution: Geocoding Based on Pairs of Toponyms

Jacques Fize, Ludovic Moncla, Bruno Martins
2021 ISPRS International Journal of Geo-Information  
., inclusion and proximity of places based on Geonames data).  ...  The proposed approach is based on a deep neural network that uses Long Short-Term Memory (LSTM) units to produce representations from sequences of character n-grams.  ...  In order to be compatible with the neural network, we need to assign each n-gram to a row in an embedding matrix, which contains vector representations for a defined vocabulary, e.g., a set of words or  ... 
doi:10.3390/ijgi10120818 fatcat:sttddeumfbg4lnkjm4tptfrzr4

Using contexts and constraints for improved geotagging of human trafficking webpages

Rahul Kapoor, Mayank Kejriwal, Pedro Szekely
2017 Proceedings of the Fourth International ACM Workshop on Managing and Mining Enriched Geo-Spatial Data - GeoRich '17  
In this paper, we describe a geotag extraction framework in which context, constraints and the openly available Geonames knowledge base work in tandem in an Integer Linear Programming (ILP) model to achieve  ...  is given by: c-population i = C pop /K (1) where K is a constant population factor (for normalization purposes) and C pop is the city population, which is obtained from Geonames.  ...  Recent advances in information extraction and knowledge base construction technology, especially using techniques like deep neural networks and word embeddings [9] , [2] , gives investigators (such as  ... 
doi:10.1145/3080546.3080547 dblp:conf/sigmod/KapoorKS17 fatcat:alwhn2sdxrb2xphqtkqjezbypu

Adaptive Geoparsing Method for Toponym Recognition and Resolution in Unstructured Text

Edwin Aldana-Bobadilla, Alejandro Molina-Villegas, Ivan Lopez-Arevalo, Shanel Reyes-Palacios, Victor Muñiz-Sanchez, Jean Arreola-Trapala
2020 Remote Sensing  
We propose an assessment measure based on a ranking of closeness relative to the predicted and actual locations of a place name.  ...  In this paper, we propose an extensible geoparsing approach including geographic entity recognition based on a neural network model and disambiguation based on what we have called dynamic context disambiguation  ...  neural network for a binary classification (geographic entity or not).  ... 
doi:10.3390/rs12183041 doaj:2a94e8c05d16492f856aa3ed81fb4916 fatcat:odfrdlic2fa37ahqtpx624c7wa

Geoparsing: Solved or Biased? An Evaluation of Geographic Biases in Geoparsing

Zilong Liu, Krzysztof Janowicz, Ling Cai, Rui Zhu, Gengchen Mai, Meilin Shi
2022 AGILE: GIScience Series  
Geoparsing, the task of extracting toponyms from texts and associating them with geographic locations, has witnessed remarkable progress over the past years.  ...  We also carry out a comparative experiment showing that stateof- the-art geoparsers developed with neural networks do not necessarily outperform the off-the-shelf tools across geographic space.  ...  As many regions of the world are sparsely populated with annotated locations in LGL and GeoVirus, we only provide measurements for global-scale evaluation corpora used in our spatially-explicit performance  ... 
doi:10.5194/agile-giss-3-9-2022 fatcat:4h5wuwy32zdvtlrb75fz4qeoky

How can voting mechanisms improve the robustness and generalizability of toponym disambiguation? [article]

Xuke Hu, Yeran Sun, Jens Kersten, Zhiyong Zhou, Friederike Klan, Hongchao Fan
2022 arXiv   pre-print
Kulkarni et al. (2020) Yan et al. (2021) proposed LGGeoCoder, which uses also global context features, including topic embedding and location embedding.  ...  We implement the approach by searching for all the candidates of a toponym from GeoNames and selecting the one with the largest population.  ... 
arXiv:2209.08286v1 fatcat:ui3swgviyfgrlj63jpxzwq3ihi
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