Zhijuan Wang^1,2, Xiaobin Zhao^1,2, Wei Song^1,*, Antai Wang³

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 213-225, 2019, DOI:10.32604/cmc.2019.05690

Abstract Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a new readability assessment formula. Experiment… More >

Suzhen Wang¹, Lu Zhang¹, Yanpiao Zhang¹, Jieli Sun¹, Chaoyi Pang², Gang Tian³, Ning Cao^4,*

CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 603-619, 2018, DOI:10.32604/cmc.2018.03884

Abstract Natural language semantic construction improves natural language comprehension ability and analytical skills of the machine. It is the basis for realizing the information exchange in the intelligent cloud-computing environment. This paper proposes a natural language semantic construction method based on cloud database, mainly including two parts: natural language cloud database construction and natural language semantic construction. Natural Language cloud database is established on the CloudStack cloud-computing environment, which is composed by corpus, thesaurus, word vector library and ontology knowledge base. In this section, we concentrate on the pretreatment of corpus and the presentation of background knowledge ontology, and then put… More >

Lingyun Xiang^1,2, Yan Li², Wei Hao^3,*, Peng Yang⁴, Xiaobo Shen⁵

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 541-559, 2018, DOI: 10.3970/cmc.2018.03510

Abstract For protecting the copyright of a text and recovering its original content harmlessly, this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution operations. By analyzing relative frequencies of synonymous words, synonyms employed for carrying payload are quantized into an unbalanced and redundant binary sequence. The quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional data. Then, the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible manner. On the receiver side, the watermark and… More >