semantic造句
241. Semantic relevancy computation is used to solve structural disambiguity in parsing syntactic.
242. We shall often find correlation between grammatical and semantic categories.
243. Based on semantic field theory, relational semantics and the nature of L2 writing, this paper proposes an L2 writing process model in the hope of seeking an effective method in teaching L2 writing.
244. The main performance of semantics variation characteristic of popular words is: The semantic mapping, the other semantic interpretation and the semantic ambiguity and so on.
245. For text analysis pLSA (Probability Latent Semantic Analysis) of Matlab algorithms, with test data and algorithm theory description.
246. This article approaches neologism from the angle of semantic extension.
247. Second, the current answer extraction approaches are usually based on statistic method, which ignores the semantic of sentences, and thus influences the accuracy of the result.
248. At the same the, th e validity in the system is set ap art to the validity of syntax and semantics, they can be judged by the way of formal proof and semantic analysis.
249. AIG extends a DTD by semantic attribute, semantic rule and constraints.
250. From the point of pan semantic analysis, this paper identifies two categories of the semantic structure of nouns: the involved semantic component and the descriptive semantic component.
251. This paper proposes a new method based on bicharacteristic fusion of answer pattern and semantic features.
252. This paper provides a Maintaining WAP Site Crawler system. This system can automatically traverse the WAP site, parse every page in the site and check syntax and semantic faults.
253. A multiclass text categorization model based on latent semantic analysis and support vector machine is researched and designed to enhance the accuracy of categorization.
254. We can take the changes of society as the basis, semantic extension and pragmatic extension as the approach and the emergence of neologism as the result.
255. That is to say, a lot of problems concerning semantic processing theory and technology of CBVR need a further study.
256. Semantic relations are much more important than syntactic markers or connectors.
257. The thesis contrasts cooking words in two aspects: degree of lexicalization and cooking semantic fields.
258. The computer aided tax system described in this thesis is a semantic grammar system, with the semantic dependency tree as the intermediate language.
259. This paper introduces semantic computation into our Chinese Question - Answering system.
260. Contrasting with traditional similarity model of word frequency, an automatic question answering system based on weighted semantic similarity model is proposed and implemented in this paper.
261. This paper introduces semantic computation into our Chinese question-answering system.
262. Using the methods of natural classifying and matched-words semantic decision, the pa- per further probed into the conceptual structure of Chinese kinship words.
263. Semantic mismatches and incompatible data formats are a staple of data integration and are not likely to vanish.
264. For better efficiency and accuracy, it needs semantic match between grid services to implement the service discovery, the service query, and the dynamic allocation and replacement of service.
265. Due to the uncertainty of the natural language meaning and difficulties of the semantic formalization, semantic processing becomes the key problem of Natural Language Processing.
266. The knowledge of semantics is the core, of which the most basic and most important one is the semantic knowledge of vocabulary.
267. The architecture identifies three types of information services: business information services, semantic/logical services, and data manipulation services.
268. Coherence has always been one focus of study in modern linguistics. The studies on coherence undergo three main stages, namely semantic, pragmatic, and pragma–cognitive.
269. These situations often call for special schemas defining information for every specific error, thus effectively extending domain semantic model to describe failure scenarios.
270. Catchwords are noted for their novelty, high frequency, analogical structure, as well as for being trendy and eye-catching. These features bring about semantic uncertainness.
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