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Relevant bibliographies by topics / System entity

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Academic literature on the topic 'System entity'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "System entity"

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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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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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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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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Dissertations / Theses on the topic "System entity"

1

Crawley, Stephen Christopher. "The entity system : an object-based filing system." Thesis, University of Cambridge, 1986. https://www.repository.cam.ac.uk/handle/1810/250882.

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Veselý, Mikuláš. "Simulace chodu podniku Prádelna Lety." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-81880.

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This diploma thesis deals with the theme simulation models. It is separated to three parts: theoretic, a part describing a simulation program and a practical part. The opening part's role is to introduce to a reader the problem about simulation models, inform him about simulation project building and define some key words. The second part explains a work with simulation program Simprocess. In the third part the reader finds out, how to use theoretic knowledge. It is demonstrated on the simulation of the operations of the company Prádelna Lety. A goal of this part is to make a simulation model, which describes the reality and can solve the main problems identified in the beginning of this part. All of this is the object of the analysis. After that is possible to give some advises about improving the operations.

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Hansen, Hugo, and Oliver Öhrström. "Benchmarking and Analysis of Entity Referencing Within Open-Source Entity Component Systems." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20074.

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Runtime performance is essential for real time games, the faster a game can run the more features designers can put into the game to accomplish their vision.A popular architecture for video games is the Entity Component System architecture aimed to improve both object composition and performance. There are many tests for how this architecture performs under its optimal linear execution.This thesis presents a performance comparison of how several popular open-source Entity Component System libraries perform when fetching data from other entities during iteration. An object-oriented test is also done to compare against and verify if the known drawbacks of object-orientation can still be seen within these test cases. Our results show that doing a random lookup during iteration can cause magnitudes worse performance for Entity Component Systems.

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Seviṇc, Süleyman 1960. "ENTITY STRUCTURE REPRESENTATION FOR LOCAL AREA NETWORK SIMULATION (SYSTEM, EXPERT)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/275551.

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Kelly, Michael Robert 1953. "Intelligent space laboratory organizational design using system entity structure concepts." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/291985.

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This thesis is the product of a knowledge acquisition effort, whose objective was to obtain information essential to the modelling and simulation of a robotically operated laboratory on board the forthcoming space station "Freedom." The information is represented using the system entity structure, a knowledge representation scheme that utilizes artificial intelligence concepts. The system entity structure details the design information and associated knowledge required for the intelligent autonomous operation of the space-based laboratory. The approach is proven to be very beneficial for organizing and displaying the vast amounts of information that constitute this intricate system design. Knowledge management, representation, and the nature of a future software implementation are also addressed.

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Elsebai, A. "A rules based system for named entity recognition in modern standard Arabic." Thesis, University of Salford, 2009. http://usir.salford.ac.uk/14925/.

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The amount of textual information available electronically has made it difficult for many users to find and access the right information within acceptable time. Research communities in the natural language processing (NLP) field are developing tools and techniques to alleviate these problems and help users in exploiting these vast resources. These techniques include Information Retrieval (IR) and Information Extraction (IE). The work described in this thesis concerns IE and more specifically, named entity extraction in Arabic. The Arabic language is of significant interest to the NLP community mainly due to its political and economic significance, but also due to its interesting characteristics. Text usually contains all kinds of names such as person names, company names, city and country names, sports teams, chemicals and lots of other names from specific domains. These names are called Named Entities (NE) and Named Entity Recognition (NER), one of the main tasks of IE systems, seeks to locate and classify automatically these names into predefined categories. NER systems are developed for different applications and can be beneficial to other information management technologies as it can be built over an IR system or can be used as the base module of a Data Mining application. In this thesis we propose an efficient and effective framework for extracting Arabic NEs from text using a rule based approach. Our approach makes use of Arabic contextual and morphological information to extract named entities. The context is represented by means of words that are used as clues for each named entity type. Morphological information is used to detect the part of speech of each word given to the morphological analyzer. Subsequently we developed and implemented our rules in order to recognise each position of the named entity. Finally, our system implementation, evaluation metrics and experimental results are presented.

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Bhattad, Pradnya Brijmohan, MohD Ibrahim, Omer Sheikh, and Debalina Das. "Plesimonas Shigelloides Induced Crohn’s Disease Flare-A Rare Entity." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/asrf/2021/presentations/50.

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Crohn’s disease is an inflammatory bowel disease that may involve any part of the gastrointestinal tract with a variety of extraintestinal features. A flare of Crohn’s disease may present as partial small bowel obstruction or peritonitis. Dehydration, infectious agents, and cigarette smoking are some of the factors linked to a relapse of Crohn’s disease. Plesimonas Shigelloides, a bacterium that belongs to the enterobacteriaceae group may rarely lead to a flare of Crohn’s disease. We describe the case of a 31-year-old male with Crohn’s disease who developed a flare triggered by Plesimonas Shigelloides infection presenting as partial small bowel obstruction with ileal narrowing, and regional lymphadenopathy that responded to immunosuppressants.

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Alanazi, Saad. "A Named Entity Recognition system applied to Arabic text in the medical domain." Thesis, Staffordshire University, 2017. http://eprints.staffs.ac.uk/3129/.

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Currently, 30-35% of the global population uses the Internet. Furthermore, there is a rapidly increasing number of non-English language internet users, accompanied by an also increasing amount of unstructured text online. One area replete with underexploited online text is the Arabic medical domain, and one method that can be used to extract valuable data from Arabic medical texts is Named Entity Recognition (NER). NER is the process by which a system can automatically detect and categorise Named Entities (NE). NER has numerous applications in many domains, and medical texts are no exception. NER applied to the medical domain could assist in detection of patterns in medical records, allowing doctors to make better diagnoses and treatment decisions, enabling medical staff to quickly assess a patient's records and ensuring that patients are informed about their data, as just a few examples. However, all these applications would require a very high level of accuracy. To improve the accuracy of NER in this domain, new approaches need to be developed that are tailored to the types of named entities to be extracted and categorised. In an effort to solve this problem, this research applied Bayesian Belief Networks (BBN) to the process. BBN, a probabilistic model for prediction of random variables and their dependencies, can be used to detect and predict entities. The aim of this research is to apply BBN to the NER task to extract relevant medical entities such as disease names, symptoms, treatment methods, and diagnosis methods from modern Arabic texts in the medical domain. To achieve this aim, a new corpus related to the medical domain has been built and annotated. Our BBN approach achieved a 96.60% precision, 90.79% recall, and 93.60% F-measure for the disease entity, while for the treatment method entity, it achieved 69.33%, 70.99%, and 70.15% for precision, recall, and F-measure, respectively. For the diagnosis method and symptom categories, our system achieved 84.91% and 71.34%, respectively, for precision, 53.36% and 49.34%, respectively, for recall, and 65.53% and 58.33%, for F-measure, respectively. Our BBN strategy achieved good accuracy for NEs in the categories of disease and treatment method. However, the average word length of the other two NE categories observed, diagnosis method and symptom, may have had a negative effect on their accuracy. Overall, the application of BBN to Arabic medical NER is successful, but more development is needed to improve accuracy to a standard at which the results can be applied to real medical systems.

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Chen, Cheng. "A system to support clerical review, correction and confirmation assertions in entity identity information management." Thesis, University of Arkansas at Little Rock, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3711495.

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Clerical review of Entity Resolution(ER) is crucial for maintaining the entity identity integrity of an Entity Identity Information Management (EIIM) system. However, the clerical review process presents several problems. These problems include Entity Identity Structures (EIS) that are difficult to read and interpret, excessive time and effort to review large Identity Knowledgebase (IKB), and the duplication of effort in repeatedly reviewing the same EIS in same EIIM review cycle or across multiple review cycles. Although the original EIIM model envisioned and demonstrated the value of correction assertions, these are applied to correct errors after they have been found. The original EIIM design did not focus on the features needed to support the process of clerical review needed to find these errors.

The research presented here extends and enhances the original EIIM model in two very significant ways. The first is a design for a pair of confirmation assertions that complement the original set of correction assertions. The confirmation assertions confirm correct linking decisions so that they can be excluded from further clerical review. The second is a design and demonstration of a comprehensive visualization system that supports clerical review, and both correction and confirmation assertion configurations in EIIM. This dissertation also describes how the confirmation assertions and the new visualization system have been successfully integrated into the OYSTER open source EIIM framework.

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Chau, Ting-Hey. "Translation Memory System Optimization : How to effectively implement translation memory system optimization." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-169218.

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Translation of technical manuals is expensive, especially when a larger company needs to publish manuals for their whole product range in over 20 different languages. When a text segment (i.e. a phrase, sentence or paragraph) is manually translated, we would like to reuse these translated segments in future translation tasks. A translated segment is stored with its corresponding source language, often called a language pair in a Translation Memory System. A language pair in a Translation Memory represents a Translation Entry also known as a Translation Unit. During a translation, when a text segment in a source document matches a segment in the Translation Memory, available target languages in the Translation Unit will not require a human translation. The previously translated segment can be inserted into the target document. Such functionality is provided in the single source publishing software, Skribenta developed by Excosoft. Skribenta requires text segments in source documents to find an exact or a full match in the Translation Memory, in order to apply a translation to a target language. A full match can only be achieved if a source segment is stored in a standardized form, which requires manual tagging of entities, and often reoccurring words such as model names and product numbers. This thesis investigates different ways to improve and optimize a Translation Memory System. One way was to aid users with the work of manual tagging of entities, by developing Heuristic algorithms to approach the problem of Named Entity Recognition (NER). The evaluation results from the developed Heuristic algorithms were compared with the result from an off the shelf NER tool developed by Stanford. The results shows that the developed Heuristic algorithms is able to achieve a higher F-Measure compare to the Stanford NER, and may be a great initial step to aid Excosofts’ users to improve their Translation Memories.
Översättning av tekniska manualer är väldigt kostsamt, speciellt när större organisationer behöver publicera produktmanualer för hela deras utbud till över 20 olika språk. När en text (t.ex. en fras, mening, paragraf) har blivit översatt så vill vi kunna återanvända den översatta texten i framtida översättningsprojekt och dokument. De översatta texterna lagras i ett översättningsminne (Translation Memory). Varje text lagras i sitt källspråk tillsammans med dess översättning på ett annat språk, så kallat målspråk. Dessa utgör då ett språkpar i ett översättningsminnessystem (Translation Memory System). Ett språkpar som lagras i ett översättningsminne utgör en Translation Entry även kallat Translation Unit. Om man hittar en matchning när man söker på källspråket efter en given textsträng i översättningsminnet, får man upp översättningar på alla möjliga målspråk för den givna textsträngen. Dessa kan i sin tur sättas in i måldokumentet. En sådan funktionalitet erbjuds i publicerings programvaran Skribenta, som har utvecklats av Excosoft. För att utföra en översättning till ett målspråk kräver Skribenta att text i källspråket hittar en exakt matchning eller en s.k. full match i översättningsminnet. En full match kan bara uppnås om en text finns lagrad i standardform. Detta kräver manuell taggning av entiteter och ofta förekommande ord som modellnamn och produktnummer. I denna uppsats undersöker jag hur man effektivt implementerar en optimering i ett översättningsminnessystem, bland annat genom att underlätta den manuella taggningen av entitier. Detta har gjorts genom olika Heuristiker som angriper problemet med Named Entity Recognition (NER). Resultat från de utvecklade Heuristikerna har jämförts med resultatet från det NER-verktyg som har utvecklats av Stanford. Resultaten visar att de Heuristiker som jag utvecklat uppnår ett högre F-Measure jämfört med Stanford NER och kan därför vara ett bra inledande steg för att hjälpa Excosofts användare att förbättra deras översättningsminnen.

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Books on the topic "System entity"

1

Crawley, Stephen Christopher. The entity system an object based filing system. Cambridge: University of Cambridge, Computer Laboratory, 1986.

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Richard, Fuller, and Koutsoukos Xenofon D, eds. Mobile entity localization and tracking in GPS-less environnments: Second international workshop, MELT 2009, Orlando, Fl, USA, September 30, 2009 : proceedings. Berlin: Springer, 2009.

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Zuo wei zu zhi shou duan de gong fa ren zhi du yan jiu: Study on the system of public legal entity as organizing means. Beijing Shi: Zhongguo zheng fa da xue chu ban she, 2009.

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Office, General Accounting. Patent and Trademark Office: Impact of higher patent fees on small-entity and federal agency users : briefing report to the Chairman, Subcommittee on Intellectual Property and Judicial Administration, Committee on the Judiciary, House of Representatives. Washington, D.C: The Office, 1991.

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Thalheim, Bernhard. Entity-Relationship Modeling: Foundations of Database Technology. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000.

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Pavlov, V. S. Overhauling the entire system of prices. Moscow: Novosti Press Agency Pub. House, 1987.

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Varlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

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Lowery, Andrew. Medical device quality systems manual: A small entity compliance guide. Rockville, Md: U.S. Dept. of Health and Human Services, Public Health Service, Food and Drug Administration, Center for Devices and Radiological Health, 1996.

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Judy, Strojny, Puleo Joseph, and Center for Devices and Radiological Health (U.S.). Division of Small Manufacturers Assistance, eds. Medical device quality systems manual: A small entity compliance guide. Rockville, Md: U.S. Dept. of Health and Human Services, Public Health Service, Food and Drug Administration, Center for Devices and Radiological Health, 1996.

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1961-, Pernul G., and Tjoa A. Min, eds. Entity-relationship approach--ER '92: 11th International Conference on the Entity-Relationship Approach, Karlsruhe, Germany, October 7-9, 1992 : proceedings. Berlin: Springer-Verlag, 1992.

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Book chapters on the topic "System entity"

1

Zeigler, Bernard P., and Hessam S. Sarjoughian. "System Entity Structure Basics." In Guide to Modeling and Simulation of Systems of Systems, 31–42. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64134-8_3.

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Zeigler, Bernard P. "System Entity Structure List." In Guide to Modeling and Simulation of Systems of Systems, 13–28. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4570-7_2.

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Zeigler, Bernard P., and Hessam S. Sarjoughian. "System Entity Structure Basics." In Guide to Modeling and Simulation of Systems of Systems, 27–37. London: Springer London, 2013. http://dx.doi.org/10.1007/978-0-85729-865-2_3.

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Kim, Young-Soo, Sung-Ja Choi, Gang-Soo Lee, and Geuk Lee. "Entity Based Message Authentication System." In Agent and Multi-Agent Systems: Technologies and Applications, 948–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72830-6_100.

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Delaney, W., M. P. Roccotelli, and E. Vaccari. "General Entity Structures for System Analysis." In Cybernetics and Systems ’86, 95–101. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4634-7_13.

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Chen, Chen, Huilin Liu, Junchang Xin, Tiezheng Nie, and Zhiqiang Pang. "ELS: An Efficient Entity Linking System." In Lecture Notes in Computer Science, 497–502. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41230-1_43.

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Morsi, Magdi M. A., and Shamkant B. Navathe. "Application and system prototyping via an extensible object-oriented environment." In Entity-Relationship Approach — ER '93, 24–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/bfb0024354.

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Wiederhold, Gio. "Modeling and system maintenance." In OOER '95: Object-Oriented and Entity-Relationship Modeling, 1–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0020516.

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Zhang, Xinru, Huifang Xu, Yixin Cao, Yuanpeng Tan, Lei Hou, Juanzi Li, and Jiaxin Shi. "DSEL: A Domain-Specific Entity Linking System." In Semantic Technology, 146–61. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41407-8_10.

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Zhang, Jing, Yixin Cao, Lei Hou, Juanzi Li, and Hai-Tao Zheng. "XLink: An Unsupervised Bilingual Entity Linking System." In Lecture Notes in Computer Science, 172–83. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69005-6_15.

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Conference papers on the topic "System entity"

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Nicolai, Garrett, Bradley Hauer, Mohammad Salameh, Adam St Arnaud, Ying Xu, Lei Yao, and Grzegorz Kondrak. "Multiple System Combination for Transliteration." In Proceedings of the Fifth Named Entity Workshop. Stroudsburg, PA, USA: Association for Computational Linguistics, 2015. http://dx.doi.org/10.18653/v1/w15-3911.

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Kulkarni, Ashish, Kanika Agarwal, Pararth Shah, Sunny Raj Rathod, and Ganesh Ramakrishnan. "System for collective entity disambiguation." In the first international workshop. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2633211.2639488.

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Folkman, Tyler, Rey Furner, and Drew Pearson. "GenERes: A Genealogical Entity Resolution System." In 2018 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2018. http://dx.doi.org/10.1109/icdmw.2018.00079.

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Druzhkina, Anna, Alexey Leontyev, and Maria Stepanova. "German NER with a Multilingual Rule Based Information Extraction System: Analysis and Issues." In Proceedings of the Sixth Named Entity Workshop. Stroudsburg, PA, USA: Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-2704.

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Gan, Yong, Yuanbo Liu, Helin Zhang, and Dongwei Jia. "Network Entity Landmark Mining Technology." In 2020 6th International Symposium on System and Software Reliability (ISSSR). IEEE, 2020. http://dx.doi.org/10.1109/isssr51244.2020.00020.

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Heinzerling, Benjamin, and Michael Strube. "Visual Error Analysis for Entity Linking." In Proceedings of ACL-IJCNLP 2015 System Demonstrations. Stroudsburg, PA, USA: Association for Computational Linguistics and The Asian Federation of Natural Language Processing, 2015. http://dx.doi.org/10.3115/v1/p15-4007.

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Waluyo, Agustinus Borgy, Feng Zhu, David Taniar, Bala Srinivasan, and Wenny Rahayu. "Multiple Entity Types Wireless Broadcast Database System." In 21st International Conference on Advanced Networking and Applications. IEEE, 2007. http://dx.doi.org/10.1109/aina.2007.95.

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Saehoon Cheon, Doohwan Kim, and Bernard P. Zeigler. "DEVS model composition by system entity structure." In 2008 IEEE International Conference on Information Reuse and Integration. IEEE, 2008. http://dx.doi.org/10.1109/iri.2008.4583078.

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Zirikly, Ayah, and Mona Diab. "Named Entity Recognition System for Dialectal Arabic." In Proceedings of the EMNLP 2014 Workshop on Arabic Natural Language Processing (ANLP). Stroudsburg, PA, USA: Association for Computational Linguistics, 2014. http://dx.doi.org/10.3115/v1/w14-3610.

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Yao, Tianfang, and Hans Uszkoreit. "Chinese named entity and relation identification system." In the COLING/ACL. Morristown, NJ, USA: Association for Computational Linguistics, 2006. http://dx.doi.org/10.3115/1225403.1225413.

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Reports on the topic "System entity"

1

Partridge, C., and G. Trewitt. High-level Entity Management System (HEMS). RFC Editor, October 1987. http://dx.doi.org/10.17487/rfc1021.

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Esplln, Timothy H., and David A. Greschka. F-16 Multitask Trainer/Weapon System Trainer Entity Limit Upgrade. Fort Belvoir, VA: Defense Technical Information Center, November 1996. http://dx.doi.org/10.21236/ada459601.

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Montierth, B. S. Time card entry system. Office of Scientific and Technical Information (OSTI), May 1996. http://dx.doi.org/10.2172/238526.

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4

Cleary, A., S. Smith, T. Vassilevska, and D. Jefferson. Scalable Entity-Based Modeling of Population-Based Systems, Final LDRD Report. Office of Scientific and Technical Information (OSTI), January 2005. http://dx.doi.org/10.2172/917499.

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5

PRAISSMAN, J. L. SUTHERLAND,J C. LABORATORY VOICE DATA ENTRY SYSTEM. Office of Scientific and Technical Information (OSTI), April 2003. http://dx.doi.org/10.2172/15006728.

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NAVAL POSTGRADUATE SCHOOL MONTEREY CA. Advanced Restricted Area Entry Control System (Araecs). Fort Belvoir, VA: Defense Technical Information Center, June 2014. http://dx.doi.org/10.21236/ada608069.

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7

Sergio Puig, J.S.D., Sergio Puig, J. S. D. Big data and the law: should we graph the entire justice system? Experiment, February 2014. http://dx.doi.org/10.18258/1980.

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Clever, J. J., L. H. Arakaki, F. M. Monaco, L. E. Juarros, and G. R. Quintana. Integrated alarm annunciation and entry control systems -- Survey results. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10132517.

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Kolkman, O., J. Schlyter, and E. Lewis. Domain Name System KEY (DNSKEY) Resource Record (RR) Secure Entry Point (SEP) Flag. RFC Editor, April 2004. http://dx.doi.org/10.17487/rfc3757.

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Haber, Stephen, and Aldo Musacchio. These Are the Good Old Days: Foreign Entry and the Mexican Banking System. Cambridge, MA: National Bureau of Economic Research, January 2013. http://dx.doi.org/10.3386/w18713.

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