disambiguation造句
1. Word sense disambiguation may be seen as a knowledge-intensive problem.
2. But in actuality, disambiguation is not unprincipled and random; rather, it is usually quite predictable.
3. Cross reference - which requires the disambiguation of word senses in the definitions to control the spread of activation caused by cross-referencing.
4. For other uses, see Bel canto ( disambiguation ).
5. For other uses, see Turkish Delight ( disambiguation ).
6. A new method of polysemant meaning disambiguation is provided.
7. For other uses, see Panda (disambiguation) and Panda Bear (disambiguation).
8. Syntacticambiguity disambiguation and target - language generation treatment are two important stages of hybrid Chinese - English machine translation.
9. In this thesis, we proposed a novel authorship disambiguation approach to solve the information shortage problem and the information ambiguity problem.
10. The bottleneck of word sense disambiguation ( WSD ) is lack of large scale, high - quality word sense annotated corpus.
11. Word Sense Disambiguation ( WSD ) is a difficult issue in many fields of natural language processing, e.
12. On the basis of this formalized system, NLP-oriented disambiguation knowledge along with its representation formulism and application strategy is given.
13. Word sense disambiguation is one of the difficult problems in natural language processing.
14. Word Sense Disambiguation ( WSD ) is a difficult issue in many fields, e.
15. Besides maximum matching, many other disambiguation algorithms have been proposed. Various information are used in the disambiguation process.
16. It has no general knowledge source to aid the process of disambiguation.
17. With the limitation of the natural language understanding technique today, lots of polyphone disambiguation algorithms are rule-based.
18. Parallel corpus has valuable application in machine translation, bilingual dictionary compilation, word sense disambiguation and Cross-Lingual Information Retrieval.
19. The range of polysemous words as the object of the computer automatic word sense disambiguation is delimited.
20. Then the main algorithm for the method of example - based disambiguation is proposed with detail.
21. This paper presents a description of the method of example - based Chinese syntactic structure disambiguation method.
22. Further more, the approach combines the advantage of human work and computer's computing power, which ensures the stability and efficiency of the construction of disambiguation rules for polyphone.
23. Chapter Four provides a relevance theoretical account for human disambiguation from the aspects of intention recognition, relevance expectation and processing effort.
24. Especially , because there a great number of a text , this problem in word sense disambiguation worse.
25. In Text-to-Speech(TTS) systems, Grapheme-Phoneme(G2P) conversion is one of the most important modules, and polyphone disambiguation is its key problem.