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Journal articles on the topic 'System entity'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Karam, Shiekha Ali, Ali Jaoua, and Samir Elloumi. "Arabic named entity operational recognition system." Qatar Foundation Annual Research Forum Proceedings, no. 2012 (October 2012): CSP37. http://dx.doi.org/10.5339/qfarf.2012.csp37.

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Chaudhari, Sneha, Amos Azaria, and Tom Mitchell. "An entity graph based Recommender System." AI Communications 30, no. 2 (May 16, 2017): 141–49. http://dx.doi.org/10.3233/aic-170728.

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Liu, Chen, Feng Li, Xian Sun, and Hongzhe Han. "Attention-Based Joint Entity Linking with Entity Embedding." Information 10, no. 2 (February 1, 2019): 46. http://dx.doi.org/10.3390/info10020046.

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Entity linking (also called entity disambiguation) aims to map the mentions in a given document to their corresponding entities in a target knowledge base. In order to build a high-quality entity linking system, efforts are made in three parts: Encoding of the entity, encoding of the mention context, and modeling the coherence among mentions. For the encoding of entity, we use long short term memory (LSTM) and a convolutional neural network (CNN) to encode the entity context and entity description, respectively. Then, we design a function to combine all the different entity information aspects, in order to generate unified, dense entity embeddings. For the encoding of mention context, unlike standard attention mechanisms which can only capture important individual words, we introduce a novel, attention mechanism-based LSTM model, which can effectively capture the important text spans around a given mention with a conditional random field (CRF) layer. In addition, we take the coherence among mentions into consideration with a Forward-Backward Algorithm, which is less time-consuming than previous methods. Our experimental results show that our model obtains a competitive, or even better, performance than state-of-the-art models across different datasets.

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4

Ling, Xiao, Sameer Singh, and Daniel S. Weld. "Design Challenges for Entity Linking." Transactions of the Association for Computational Linguistics 3 (December 2015): 315–28. http://dx.doi.org/10.1162/tacl_a_00141.

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Recent research on entity linking (EL) has introduced a plethora of promising techniques, ranging from deep neural networks to joint inference. But despite numerous papers there is surprisingly little understanding of the state of the art in EL. We attack this confusion by analyzing differences between several versions of the EL problem and presenting a simple yet effective, modular, unsupervised system, called Vinculum, for entity linking. We conduct an extensive evaluation on nine data sets, comparing Vinculum with two state-of-the-art systems, and elucidate key aspects of the system that include mention extraction, candidate generation, entity type prediction, entity coreference, and coherence.

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Kalender, Murat, and Emin Erkan Korkmaz. "THINKER - Entity Linking System for Turkish Language." IEEE Transactions on Knowledge and Data Engineering 30, no. 2 (February 1, 2018): 367–80. http://dx.doi.org/10.1109/tkde.2017.2761743.

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Kim, T. G., C. Lee, E. R. Christensen, and B. P. Zeigler. "System entity structuring and model base management." IEEE Transactions on Systems, Man, and Cybernetics 20, no. 5 (1990): 1013–24. http://dx.doi.org/10.1109/21.59966.

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Partridge, C., and G. Trewitt. "The high-level entity management system (HEMS)." IEEE Network 2, no. 2 (March 1988): 37–42. http://dx.doi.org/10.1109/65.3257.

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8

Chan, Hock C. "An entity relationship menu system for microcomputers." Journal of Microcomputer Applications 16, no. 1 (January 1993): 85–106. http://dx.doi.org/10.1006/jmca.1993.1007.

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9

Sarkar, Kamal. "Hindi named entity recognition using system combination." International Journal of Applied Pattern Recognition 5, no. 1 (2018): 11. http://dx.doi.org/10.1504/ijapr.2018.090519.

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Sarkar, Kamal. "Hindi named entity recognition using system combination." International Journal of Applied Pattern Recognition 5, no. 1 (2018): 11. http://dx.doi.org/10.1504/ijapr.2018.10011654.

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11

Kejriwal, Mayank. "Populating a linked data entity name system." AI Matters 3, no. 2 (July 13, 2017): 22–23. http://dx.doi.org/10.1145/3098888.3098897.

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Onoe, Yasumasa, and Greg Durrett. "Fine-Grained Entity Typing for Domain Independent Entity Linking." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 8576–83. http://dx.doi.org/10.1609/aaai.v34i05.6380.

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Neural entity linking models are very powerful, but run the risk of overfitting to the domain they are trained in. For this problem, a “domain” is characterized not just by genre of text but even by factors as specific as the particular distribution of entities, as neural models tend to overfit by memorizing properties of frequent entities in a dataset. We tackle the problem of building robust entity linking models that generalize effectively and do not rely on labeled entity linking data with a specific entity distribution. Rather than predicting entities directly, our approach models fine-grained entity properties, which can help disambiguate between even closely related entities. We derive a large inventory of types (tens of thousands) from Wikipedia categories, and use hyperlinked mentions in Wikipedia to distantly label data and train an entity typing model. At test time, we classify a mention with this typing model and use soft type predictions to link the mention to the most similar candidate entity. We evaluate our entity linking system on the CoNLL-YAGO dataset (Hoffart et al. 2011) and show that our approach outperforms prior domain-independent entity linking systems. We also test our approach in a harder setting derived from the WikilinksNED dataset (Eshel et al. 2017) where all the mention-entity pairs are unseen during test time. Results indicate that our approach generalizes better than a state-of-the-art neural model on the dataset.

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13

Ekbal, Asif, and Sivaji Bandyopadhyay. "Named Entity Recognition in Bengali." Northern European Journal of Language Technology 1 (February 2, 2010): 26–58. http://dx.doi.org/10.3384/nejlt.2000-1533.091226.

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This paper reports about a multi-engine approach for the development of a Named Entity Recognition (NER) system in Bengali by combining the classifiers such as Maximum Entropy (ME), Conditional Random Field (CRF) and Support Vector Machine (SVM) with the help of weighted voting techniques. The training set consists of approximately 272K wordforms, out of which 150K wordforms have been manually annotated with the four major named entity (NE) tags, namely Person name, Location name, Organization name and Miscellaneous name. An appropriate tag conversion routine has been defined in order to convert the 122K wordforms of the IJCNLP-08 NER Shared Task on South and South East Asian Languages (NERSSEAL)1 data into the desired forms. The individual classifiers make use of the different contextual information of the words along with the variety of features that are helpful to predict the various NE classes. Lexical context patterns, generated from an unlabeled corpus of 3 million wordforms in a semi-automatic way, have been used as the features of the classifiers in order to improve their performance. In addition, we propose a number of techniques to post-process the output of each classifier in order to reduce the errors and to improve the performance further. Finally, we use three weighted voting techniques to combine the individual models. Experimental results show the effectiveness of the proposed multi-engine approach with the overall Recall, Precision and F-Score values of 93.98%, 90.63% and 92.28%, respectively, which shows an improvement of 14.92% in F-Score over the best performing baseline SVM based system and an improvement of 18.36% in F-Score over the least performing baseline ME based system. Comparative evaluation results also show that the proposed system outperforms the three other existing Bengali NER systems.

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Jain, Arti, and Anuja Arora. "Named Entity System for Tweets in Hindi Language." International Journal of Intelligent Information Technologies 14, no. 4 (October 2018): 55–76. http://dx.doi.org/10.4018/ijiit.2018100104.

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Due to the growing need of smart-health applications in Hindi language, there is a rapid demand for health-related Named Entity Recognition (NER) system for Hindi. For the purpose of the same, this research considers Twitter social network to extract tweets dated 1st October 2016 to 15th October 2017 from Patanjali, Dabur and other Hindi language-oriented Twitter based health sites; while considering four NE types- Person, Disease, Consumable and Organization. To the best of its knowledge, the considered Twitter dataset and NE types for Hindi language is one of the first resources that is being taken care. This article introduces three stage NER system for Tweets in Hindi language (HinTwtNER system)- pre-processing stage; machine Learning stage (Hyperspace Analogue to Language (HAL) and Conditional Random Field (CRF)); and post-processing stage. HinTwtNER looks into binary features and achieves an overall F-score of 49.87% which is comparable to the Twitter based NER systems for English and other languages.

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15

POIBEAU, THIERRY. "BOOSTING ROBUSTNESS OF A NAMED ENTITY RECOGNIZER." International Journal of Semantic Computing 03, no. 01 (March 2009): 91–104. http://dx.doi.org/10.1142/s1793351x09000689.

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Since the Message Understanding Conferences on Information Extraction in the 80's and 90's, Named Entity ReCognition (NERC) is a well-established task in the Natural Language Processing (NLP) community. However, very different systems seem to perform very similarly when applied to the same corpus. In this paper, we present a state-of-the-art NERC system. This tool is a hybrid system, based on different resources and techniques. We then propose a protocol to "deconstruct" and evaluate the different components of a complex named entity recognition system. We examine the performance of such a system with learning capacities and reduced initial knowledge on medium-size unlabelled corpora.

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Lee, Hojun, and Bernard P. Zeigler. "System Entity Structure Ontological Data Fusion Process Integrated with C2 Systems." Journal of Defense Modeling and Simulation: Applications, Methodology, Technology 7, no. 4 (April 16, 2010): 206–25. http://dx.doi.org/10.1177/1548512910365063.

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17

Park, H. C., and T. G. Kim. "Relational algebraic system entity structure for models management." IEE Proceedings - Computers and Digital Techniques 143, no. 1 (1996): 49. http://dx.doi.org/10.1049/ip-cdt:19960166.

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18

Ekbal, Asif, and Sivaji Bandyopadhyay. "Named entity recognition in Bengali using system combination." Lingvisticæ Investigationes. International Journal of Linguistics and Language Resources 37, no. 1 (September 5, 2014): 1–22. http://dx.doi.org/10.1075/li.37.1.01ekb.

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This paper reports a voted Named Entity Recognition (NER) system that exploits appropriate unlabeled data. Initially, we develop NER systems using the supervised machine learning algorithms such as Maximum Entropy (ME), Conditional Random Field (CRF) and Support Vector Machine (SVM). Each of these models makes use of the language independent features in the form of different contextual and orthographic word-level features along with the language dependent features extracted from the Part-of-Speech (POS) tagger and gazetteers. Context patterns generated from the unlabeled data using an active learning method are also used as the features in each of the classifiers. A semi-supervised method is proposed to describe the measures to automatically select effective unlabeled documents as well as sentences from the unlabeled data. Finally, the supervised models are combined together into a final system by defining appropriate weighted voting technique. Experimental results for a resource-poor language like Bengali show the effectiveness of the proposed approach with the overall recall, precision and F-measure values of 93.81%, 92.18% and 92.98%, respectively.

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ZEIGLER, BERNARD P., CHUNGMAN SEO, and DOOHWAN KIM. "SYSTEM ENTITY STRUCTURES FOR SUITES OF SIMULATION MODELS." International Journal of Modeling, Simulation, and Scientific Computing 04, no. 03 (August 19, 2013): 1340006. http://dx.doi.org/10.1142/s1793962313400060.

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We describe how to develop a suite of models in the MS4 Modeling Environment (MS4 Me). The approach employs the operation of merging of System Entity Structures supported by the environment. After construction, the suite of models can be hosted on Model Store, the cloud-based repository of models provided by MS4 systems as a basis for further collaborative model development. A suite of models, relating to Health Care is used as an example. In this paper, we review basic concepts of the SES needed to support of suites of simulation models. We then consider the concept of multiple aspects that provides more advanced capabilities to construct and manipulate suites of models. With this background, we go on to discuss a methodology for developing suites of simulation models and cloud-based technology for storing and sharing such models in a marketplace of models. Finally, we discuss future research and developments needed to bring the marketplace into common use by modeling and simulation practitioners.

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20

Jacucci, Giulio, Pedram Daee, Tung Vuong, Salvatore Andolina, Khalil Klouche, Mats SjÖberg, Tuukka Ruotsalo, and Samuel Kaski. "Entity Recommendation for Everyday Digital Tasks." ACM Transactions on Computer-Human Interaction 28, no. 5 (October 31, 2021): 1–41. http://dx.doi.org/10.1145/3458919.

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Recommender systems can support everyday digital tasks by retrieving and recommending useful information contextually. This is becoming increasingly relevant in services and operating systems. Previous research often focuses on specific recommendation tasks with data captured from interactions with an individual application. The quality of recommendations is also often evaluated addressing only computational measures of accuracy, without investigating the usefulness of recommendations in realistic tasks. The aim of this work is to synthesize the research in this area through a novel approach by (1) demonstrating comprehensive digital activity monitoring, (2) introducing entity-based computing and interaction, and (3) investigating the previously overlooked usefulness of entity recommendations and their actual impact on user behavior in real tasks. The methodology exploits context from screen frames recorded every 2 seconds to recommend information entities related to the current task. We embodied this methodology in an interactive system and investigated the relevance and influence of the recommended entities in a study with participants resuming their real-world tasks after a 14-day monitoring phase. Results show that the recommendations allowed participants to find more relevant entities than in a control without the system. In addition, the recommended entities were also used in the actual tasks. In the discussion, we reflect on a research agenda for entity recommendation in context, revisiting comprehensive monitoring to include the physical world, considering entities as actionable recommendations, capturing drifting intent and routines, and considering explainability and transparency of recommendations, ethics, and ownership of data.

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Демин, A. Demin, Морозов, and V. Morozov. "Municipal Entities’ Life Support System: Current State, Main Threats, Anti-crisis Policy." Administration 2, no. 3 (September 17, 2014): 62–70. http://dx.doi.org/10.12737/5639.

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Some questions related to analysis of theoretical concepts of "municipal entity life-support system" and "municipal entity competence" to clarify their essential characteristics, generalizations of theory and practice related to municipal entity life-support systems management and analysis of municipal entities’ competences distribution system status, to identify the main trends of its development, to develop a model of competences distribution between local authorities and a model of municipal entity life-support systems management efficiency improving.

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22

Gan, Yong, Ao Ran Sun, and Jing Chen. "System Design on 3D Entity Non-Destructive Measurement Method." Advanced Materials Research 421 (December 2011): 364–68. http://dx.doi.org/10.4028/www.scientific.net/amr.421.364.

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It discusses the measurement principle and the system design of 3D non-destructive measurement method for the homogeneous entity. The measurement project and its operating process is discussed. The basic operation principle and components of this measurement device are pointed out. It included the digitized minute entity cells and the delaminated measuring method for product profiles based on liquid. It is based on Archimedes' principle and lever principle and gravity moment, combined the equations of the gravity moment and the equations of the center of gravity, the 3D coordinate values of every minute entity cell in different layers can be reckon by computer. By inputting the 3D coordinate values of the product into the related CAD software system, the 3D model could be obtained. The principles, the system software were introduced in details about the measurement system of the homogeneous entity profiles. Proved through principium experiment, the system satisfies the request of the measuring precision. The measurement system is effective and feasible.

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23

Popova, L. V., I. A. Maslova, and E. G. Dedkova. "The formation of the information accounting system of the business entity." Voprosy regionalnoj ekonomiki 30, no. 1 (March 20, 2017): 147–51. http://dx.doi.org/10.21499/2078-4023-2017-30-1-147-151.

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The article justified the urgency and benefits of developing accounting and control systems in the enterprise. Presents the author's vision of the entity and item content information accounting and control system at the level of the entity. Defines the function of the components of information accounting and control system, the implementation of which allows to form the array of analytical data necessary for the development and management decisions.

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24

Shin, Hyung-Wook, Hyung-Jeong Yang, Soo-Hyung Kim, Guee-Sang Lee, Kyoung-Yun Kim, Sun-Hee Kim, and Do Luu Ngoc. "Heterogeneous Web Information Integration System based on Entity Identification." International Journal of Contents 8, no. 4 (December 28, 2012): 21–29. http://dx.doi.org/10.5392/ijoc.2012.8.4.021.

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Yi, Hui-Kang, Jiu-Ming Huang, and Shu-Qiang Yang. "A Chinese Named Entity Recognition System with Neural Networks." ITM Web of Conferences 12 (2017): 04002. http://dx.doi.org/10.1051/itmconf/20171204002.

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Bouquet, Paolo, and Andrea Molinari. "A global entity name system (ENS) for data ecosystems." Proceedings of the VLDB Endowment 6, no. 11 (August 27, 2013): 1182–83. http://dx.doi.org/10.14778/2536222.2536250.

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27

Hatledal, Lars I., Yingguang Chu, Arne Styve, and Houxiang Zhang. "Vico: An entity-component-system based co-simulation framework." Simulation Modelling Practice and Theory 108 (April 2021): 102243. http://dx.doi.org/10.1016/j.simpat.2020.102243.

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28

Khaled, Shafi A., and A. Wahhab Khandker. "Portfolio Determination of a Zero-Interest Financial System Entity." Islamic Economic Studies 22, no. 1 (2014): 217–32. http://dx.doi.org/10.12816/0004136.

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29

Rocktäschel, Tim, Michael Weidlich, and Ulf Leser. "ChemSpot: a hybrid system for chemical named entity recognition." Bioinformatics 28, no. 12 (April 12, 2012): 1633–40. http://dx.doi.org/10.1093/bioinformatics/bts183.

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30

Song, Y., E. Kim, G. G. Lee, and B. k. Yi. "POSBIOTM--NER: a trainable biomedical named-entity recognition system." Bioinformatics 21, no. 11 (April 6, 2005): 2794–96. http://dx.doi.org/10.1093/bioinformatics/bti414.

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31

Yuan, Soe-Tsyr Daphne, and Shiou-Tian Hsu. "Enhancing service system design: An entity interaction pattern approach." Information Systems Frontiers 19, no. 3 (October 26, 2015): 481–507. http://dx.doi.org/10.1007/s10796-015-9604-z.

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32

Lee, Yu-Wei, Chung-Feng Jeffrey Kuo, Wei-Han Weng, Chao-Yang Huang, and Cheng-Yu Peng. "Dynamic modeling and entity validation of a photovoltaic system." Applied Energy 200 (August 2017): 370–82. http://dx.doi.org/10.1016/j.apenergy.2017.04.075.

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33

Wright, Edmond. "The Entity Fallacy in Epistemology." Philosophy 67, no. 259 (January 1992): 33–50. http://dx.doi.org/10.1017/s0031819100039814.

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In order to entertain the argument to be presented here, you have to begin by casting away a presupposition. The ultimate aim will be to restore it again as a presupposition, but the immediate aim will be to test for and make clear its undoubted worth and usefulness by imagining what happens to our knowledge-system when we remove it.

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Steinberger, Ralf, and Bruno Pouliquen. "Cross-lingual Named Entity Recognition." Lingvisticæ Investigationes. International Journal of Linguistics and Language Resources 30, no. 1 (August 10, 2007): 135–62. http://dx.doi.org/10.1075/li.30.1.09ste.

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Named Entity Recognition and Classification (NERC) is a known and well-explored text analysis application that has been applied to various languages. We are presenting an automatic, highly multilingual news analysis system that fully integrates NERC for locations, persons and organisations with document clustering, multi-label categorisation, name attribute extraction, name variant merging and the calculation of social networks. The proposed application goes beyond the state-of-the-art by automatically merging the information found in news written in ten different languages, and by using the aggregated name information to automatically link related news documents across languages for all 45 language pair combinations. While state-of-the-art approaches for cross-lingual name variant merging and document similarity calculation require bilingual resources, the methods proposed here are mostly language-independent and require a minimal amount of monolingual language-specific effort. The development of resources for additional languages is therefore kept to a minimum and new languages can be plugged into the system effortlessly. The presented online news analysis application is fully functional and has, at the end of the year 2006, reached average usage statistics of 600,000 hits per day.

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35

Soloviev,, V. V., S. V. Yushkin, and S. V. Maksimov*. "Antitrust compliance: system standardization issues." Russian competition law and economy, no. 2 (August 20, 2021): 8–16. http://dx.doi.org/10.47361/2542-0259-2021-2-26-8-16.

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The article examines the etymology and prehistory of the introduction of the institution of antimonopoly compliance in Russian business practice, the relationship of this institution with the institution of general compliance. The article considers the definition of the concept of antimonopoly compliance, enshrined in the new article 91 of the Federal Law "On Protection of Competition".The authors propose their own definition of the concept of antimonopoly compliance as an activity of an economic entity aimed at ensuring compliance with antimonopoly legislation by employees of an economic entity and an economic entity as a whole by preventing and suppressing violations of the requirements of such legislation and regulatory legal and law enforcement acts based on it.The authors also substantiate the advisability of developing a special national standard GOST R "System of internal compliance with the requirements of antimonopoly legislation (antimonopoly compliance system) of an economic entity".It is noted that the effectiveness of the antimonopoly compliance system will depend not only on the ability of an economic entity to form an antimonopoly compliance system on the basis of an appropriate national standard, but also on the state's ability to determine and guarantee effective incentives to comply with antimonopoly legislation.The authors substantiate the advisability of supplementing the Code of Administrative Offenses of the Russian Federation with provisions that provide for the obligation and limits to reduce the amount of punishment or replace the punishment with a softer one in the event of an anticompetitive administrative offense by a person who has implemented an effective system of antimonopoly compliance.

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JIMÉNEZ, M. D., N. FERNÁNDEZ, J. ARIAS FISTEUS, and L. SÁNCHEZ. "WikiIdRank++: EXTENSIONS AND IMPROVEMENTS OF THE WikiIdRank SYSTEM FOR ENTITY LINKING." International Journal on Artificial Intelligence Tools 22, no. 03 (June 2013): 1350018. http://dx.doi.org/10.1142/s0218213013500188.

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The amount of information available on the Web has grown considerably in recent years, leading to the need to structure it in order to access it in a quick and accurate way. In order to develop techniques to automate the structuring process, the Knowledge Base Population (KBP) track of the Text Analysis Conference (TAC) was created. This forum aims to encourage research in automated systems capable of capturing knowledge in unstructured information. One of the tasks proposed in the context of the KBP track is named entity linking, and its goal is to link named entities mentioned in a document to instances in a reference knowledge base built from Wikipedia. This paper focuses on the entity linking task in the context of KBP 2010, where two different varieties of this task were considered, depending on whether the use of the text from Wikipedia was allowed or not. Specifically, the paper proposes a set of modifications to a system that participated in KBP 2010, named WikiIdRank, in order to improve its performance. The different modifications were evaluated in the official KBP 2010 corpus, showing that the best combination increases the accuracy of the initial system in a 7.04%. Though the resultant system, named WikiIdRank++, is unsupervised and does not take advantage of Wikipedia text, a comparison with other approaches in KBP indicates that the system would rank as 4th (out of 16) in the global comparison, outperforming other approaches that use human supervision and take advantage of Wikipedia textual contents. Furthermore, the system would rank as 1st in the category of systems that do not use Wikipedia text.

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37

Gan, Yong, Jing Ru Zhong, and Du Fen Gan. "Research on 3D Non-Destructive Measurement System Based on Homogeneous Entity." Advanced Materials Research 201-203 (February 2011): 63–68. http://dx.doi.org/10.4028/www.scientific.net/amr.201-203.63.

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A new non-destructive measurement system of the homogeneous entity profiles was designed; it included the digitized minute entity cells and the delaminated measuring method for product profiles based on liquid. It is based on Archimedes' principle and lever principle and gravity moment, used optic system to collect images and calculated the verge profiles, combined the equations of the gravity moment and the equations of the center of gravity to reckon the 3D coordinate values of every minute entity cell in different layers by computer. By inputting the 3D coordinate values of the product into the related CAD software system, the 3D model could be obtained. The principles, hardware and software of the system were introduced in details about the measurement system of the homogeneous entity profiles.

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38

Hu, Feng Ju, Ji Xin Liu, and Na Wang. "3D Creation Methods Based on User Coordinate System of AutoCAD." Advanced Materials Research 588-589 (November 2012): 1364–67. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1364.

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This paper mainly introduces the methods and advantages of creating three-dimensional entity by the user coordinate system (UCS). The example of the operation details the operation method and skill of the UCS entity . This makes the creation process of the 3D entity clear, simple, and quick.

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39

NGUYEN, Khai, and Ryutaro ICHISE. "Linked Data Entity Resolution System Enhanced by Configuration Learning Algorithm." IEICE Transactions on Information and Systems E99.D, no. 6 (2016): 1521–30. http://dx.doi.org/10.1587/transinf.2015edp7392.

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40

Chan, Ka, and Alistair Milne. "The Global Legal Entity Identifier System: How Can It Deliver?" Journal of Risk and Financial Management 12, no. 1 (March 7, 2019): 39. http://dx.doi.org/10.3390/jrfm12010039.

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We examine the global legal entity identifier (LEI) system for the identification of participants in financial markets. Semi-structured interviews with data professionals revealed the many ways in which the LEI can improve both business process efficiency, and counterparty and credit risk management. Larger social benefits, including the monitoring of systemic financial risk, are achievable if it becomes the accepted universal standard for legal entity identification. Our interviews also review the substantial co-ordination and investment barriers to LEI adoption. To address these, a clear regulatory-led road map is needed for its future development, with widespread application in regulatory reporting.

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41

A P, Ajees, and Sumam Mary Idicula. "A Named Entity Recognition System for Malayalam using Neural Networks." Procedia Computer Science 143 (2018): 962–69. http://dx.doi.org/10.1016/j.procs.2018.10.338.

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42

Li, Lishuang, Jing Zhang, Liuke Jin, Rui Guo, and Degen Huang. "A distributed meta-learning system for Chinese entity relation extraction." Neurocomputing 149 (February 2015): 1135–42. http://dx.doi.org/10.1016/j.neucom.2014.07.016.

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43

Ko, K. E., and K. B. Sim. "Real‐time object entity detection system for smart surveillance application." Electronics Letters 53, no. 19 (September 2017): 1304–6. http://dx.doi.org/10.1049/el.2017.1532.

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Fenton, S., M. R. Canninga-van Dijk, and M. Ph Mourits. "Lipogranuloma of the nasolacrimal system, an iatrogenic and preventable entity." Eye 17, no. 4 (May 2003): 528–30. http://dx.doi.org/10.1038/sj.eye.6700384.

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Krstev, C., I. Obradovi , M. Utvi , and D. Vitas. "A system for named entity recognition based on local grammars." Journal of Logic and Computation 24, no. 2 (February 19, 2013): 473–89. http://dx.doi.org/10.1093/logcom/exs079.

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Talha, Meryem, Siham Boulaknadel, and Driss Aboutajdine. "Development of Amazighe Named Entity Recognition System Using Hybrid Method." Research in Computing Science 90, no. 1 (December 31, 2015): 151–61. http://dx.doi.org/10.13053/rcs-90-1-11.

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Rose, Barry, George S. Tamvakopoulos, Eric Yeung, Robin Pollock, John Skinner, Timothy Briggs, and Steven Cannon. "Granular Cell Tumours: A Rare Entity in the Musculoskeletal System." Sarcoma 2009 (2009): 1–4. http://dx.doi.org/10.1155/2009/765927.

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Granular Cell Tumours are rare mesenchymal soft tissue tumours that arise throughout the body and are believed to be of neural origin. They often present as asymptomatic, slow-growing, benign, solitary lesions but may be multifocal. 1-2% of cases are malignant and can metastasise. Described series in the literature are sparse. We identified eleven cases in ten patients treated surgically and followed-up for a period of over 6 years in our regional bone and soft tissue tumour centre. Five tumours were located in the lower limb, four in the upper limb, and two in the trunk. Mean patient age was 31.2 years (range 8–55 years). Excision was complete in one case, marginal in five cases and intralesional in five cases. No patients required postoperative adjuvant treatment. Mean follow-up was 19.3 months (range 1–37 months). One case was multifocal, but there were no cases of local recurrence or malignancy. Histopathological and immunohistochemical analysis revealed the classical granular cell tumour features in all cases. We believe this case series to be the largest of its type in patients presenting to an orthopaedic soft tissue tumour unit. We present our findings and correlate them with findings of other series in the literature.

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Bell, Lindsey, Rajesh Chowdhary, Jun S. Liu, Xufeng Niu, and Jinfeng Zhang. "Integrated Bio-Entity Network: A System for Biological Knowledge Discovery." PLoS ONE 6, no. 6 (June 27, 2011): e21474. http://dx.doi.org/10.1371/journal.pone.0021474.

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Zou, Yuwei, Jinguang Gu, and Haidong Fu. "Medical entity and attributes extraction system based on relation annotation." Wuhan University Journal of Natural Sciences 21, no. 2 (April 2016): 145–50. http://dx.doi.org/10.1007/s11859-016-1151-z.

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Choi, Dal Nim, Jin Myoung Kim, Won Tae Kim, and Hyung Jong Kim. "XML Representation of System Entity Structure for Distributed Modeling Simulation." Advanced Materials Research 488-489 (March 2012): 892–97. http://dx.doi.org/10.4028/www.scientific.net/amr.488-489.892.

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Distributed simulation refers to the execution of a complex model on geographically dispersed simulators, and it can increase the speed of a simulation and eventually decrease the simulation execution time. The distributed simulation enables models to be executed in physically distributed position. The system entity structure (SES) is used to represent the structural relation of simulation models and there are several SES’s XML representation methods. To make use of the SES in a distributed simulation environment, the revision of existing XML representation is needed. In this paper, we propose revised XML representation for loading models dynamically in the distributed simulation environment. A template of XML representation is defined to meet a number of modeling requirements, and it shows the specific information of model’s hierarchy and coupling. Each simulator’s model loader analyzes the XML-based SES representations and loads information of a model dynamically. We validate our method using a coupled model example.

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