Knowledge (XXG)

Context model

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that focuses on understanding and incorporating contextual information from the input text. The main purpose of a context model is to provide the language model with a better understanding of the context surrounding words, phrases, or sentences, so that it can generate more coherent and contextually
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architectures to capture contextual information from the input sequence. The context model takes into account the relationships between words and their surrounding text, helping the language model understand the meaning of a word in a specific context, handle ambiguities, and generate more accurate
31:(or context modeling) defines how context data are structured and maintained (It plays a key role in supporting efficient context management). It aims to produce a formal or semi-formal description of the context information that is present in a 194:, drawing from historical and re-analysis context data. In general, the approach is to match up current conditions using past data as context and then apply a mix of physics and historical outcomes to form a projection. 129:
program. A context model used during design defines land, aquatic, or atmospheric characteristics (stated in terms of mathematical algorithms or a simulation) that the eventual product will face in the real
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system. In other words, the context is the surrounding element for the system, and a model provides the mathematical interface and a behavioral description of the surrounding environment.
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as used in systems engineering defines a context model as the physical scope of the system being designed, which could include the user as well as the environment and other actors. A
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In terms of a physical environment, a context model defines the external interfaces that a system will interact with. This type of context model has been used to create models for
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In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 128-135. Association for Computational Linguistics.
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A key role of context model is to simplify and introduce greater structure into the task of developing context-aware applications.
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Wang, Xiao Hang; Zhang, D. Qing; Gu, Tao; Pung, Hung Keng (2004). "Ontology based context modeling and reasoning using OWL".
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It is used to represent the reusable context information of the components (The top-level classes consist of
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Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops
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Proceedings of Communication Networks and Distributed Systems Modeling and Simulation Conference
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The Engineering Handbook of Smart Technology for Aging, Disability and Independence
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Delcher, A.; Harmon, D.; Kasif, S.; White, O.; Salzberg, S. L. (1999).
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Proceedings of the ACM on Human-Computer Interaction (PACMHCI), 1(1)
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Gu, Tao; Wang, Xiao Hang; Pung, Hung Keng; Zhang, Da Qing (2004).
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Component, Context, and Manufacturing Model Library – 2 (C2M2L-2)
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A context model can also apply to the surrounding elements in a
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Trullemans, Sandra; Van Holsbeeke, Lars; Signer, Beat (2017).
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Several examples of context models occur under other domains.
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Abdelsalam Helal; Mounir Mokhtari; Bessam Abdulrazak (2008).
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can provide the probabilities for the surrounding context.
137:, a context model refers to a component or aspect of the 298:"Improved microbial gene identification with GLIMMER" 215:
Rapid integration of software engineering techniques
80:, a context model defines the surrounding text of a 282:Klein, Dan, and Christopher D. (2002) Manning. 8: 170:systems that apply context models include 354: 321: 212:Nicolas Guelfi; Anthony Savidis (2006). 204: 118:of information related to the subject. 69:represents the context graphically.. 7: 25: 160:transformer (machine learning) 76:In the situation of parsing a 1: 96:rules. In the latter case, a 168:numerical weather prediction 146:-based language models like 431: 142:appropriate responses. In 57:Examples of context models 218:. Springer. p. 131. 86:context sensitive grammar 63:Unified Modeling Language 163:and coherent responses. 42:, component container, 314:10.1093/nar/27.23.4636 302:Nucleic Acids Research 243:. Wiley. p. 592. 67:system context diagram 166:Examples of AI-based 135:large language models 127:Adaptive Vehicle Make 156:attention mechanisms 123:virtual environments 98:hidden Markov model 158:and multi-layered 133:In the context of 308:(23): 4636–4641. 250:978-0-471-71155-1 116:semantic analysis 84:. This enables a 16:(Redirected from 422: 415:Systems analysis 399: 393: 387: 386: 376: 367: 361: 360: 358: 342: 336: 335: 325: 293: 287: 280: 274: 273: 272:. ACM: 7:1–7:16. 261: 255: 254: 236: 230: 229: 209: 46:requirement and 40:Operating system 21: 18:Context modeling 430: 429: 425: 424: 423: 421: 420: 419: 405: 404: 403: 402: 394: 390: 374: 369: 368: 364: 349:. IEEE: 18–22. 344: 343: 339: 295: 294: 290: 281: 277: 263: 262: 258: 251: 238: 237: 233: 226: 211: 210: 206: 201: 172:Google DeepMind 82:lexical element 59: 23: 22: 15: 12: 11: 5: 428: 426: 418: 417: 407: 406: 401: 400: 388: 362: 337: 288: 275: 256: 249: 231: 224: 203: 202: 200: 197: 196: 195: 164: 139:language model 131: 119: 108: 101: 88:that can have 58: 55: 50:requirement). 24: 14: 13: 10: 9: 6: 4: 3: 2: 427: 416: 413: 412: 410: 397: 392: 389: 384: 380: 373: 366: 363: 357: 356:10.1.1.3.9626 352: 348: 341: 338: 333: 329: 324: 319: 315: 311: 307: 303: 299: 292: 289: 285: 279: 276: 271: 267: 260: 257: 252: 246: 242: 235: 232: 227: 225:3-540-34063-7 221: 217: 216: 208: 205: 198: 193: 189: 185: 181: 177: 173: 169: 165: 161: 157: 153: 149: 145: 144:deep learning 140: 136: 132: 128: 124: 120: 117: 113: 109: 106: 105:gene sequence 102: 99: 95: 91: 90:deterministic 87: 83: 79: 75: 74: 73: 70: 68: 64: 56: 54: 51: 49: 45: 41: 36: 34: 33:context-aware 30: 29:context model 19: 391: 382: 378: 365: 346: 340: 305: 301: 291: 278: 269: 259: 240: 234: 214: 207: 184:PanguWeather 130:environment. 125:such as the 71: 60: 52: 37: 28: 26: 192:FourCastNet 385:: 270–275. 199:References 110:Within an 94:stochastic 351:CiteSeerX 176:GraphCast 409:Category 332:10556321 112:ontology 48:Software 44:hardware 78:grammar 353:  330:  323:148753 320:  247:  222:  188:NVIDIA 186:, and 180:Huawei 375:(PDF) 148:GPT-4 383:2004 328:PMID 245:ISBN 220:ISBN 152:BERT 61:The 318:PMC 310:doi 190:'s 182:'s 174:'s 150:or 92:or 411:: 381:. 377:. 326:. 316:. 306:27 304:. 300:. 268:. 178:, 27:A 359:. 334:. 312:: 253:. 228:. 20:)

Index

Context modeling
context-aware
Operating system
hardware
Software
Unified Modeling Language
system context diagram
grammar
lexical element
context sensitive grammar
deterministic
stochastic
hidden Markov model
gene sequence
ontology
semantic analysis
virtual environments
Adaptive Vehicle Make
large language models
language model
deep learning
GPT-4
BERT
attention mechanisms
transformer (machine learning)
numerical weather prediction
Google DeepMind
GraphCast
Huawei
PanguWeather

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