best natural language processing books

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Basic Data Types in data processing language

Different programming languages have different basic data types depending on their design purposes. Java, C #, and other languages are designed for general application development. The basic data types are string, number, Boolean, and other atomic data types, as well as arrays and common objects. SQL, PowerBuilder, R, and esproc are designed for data processing. The basic data type is a structured two-dimensional data table object. For example, this S

[Language Processing and Python] 6.4 decision tree/6.5 Naive Bayes classifier/6.6 Maximum Entropy Classifier

, features) Maximum Entropy Model The maximum entropy classifier model is a generalization of the naive Bayes classifier model. The following content is taken from: http://wiki.52nlp.cn/%E6%9C%80%E5%A4%A7%E7%86%B5%E6%A8%A1%E5%9E%8B%E4%B8%8E%E8%87%AA%E7%84%B6%E8%AF%AD%E8%A8%80%E5%A4%84%E7%90%86 Maximum Entropy Model and Natural Language Processing In daily li

Application of Hidden Markov model in language processing

Finally determined to understand the Markov chain. Of course, the classic of the tutorial will be the reference document, in addition to find a professor of Zhejiang University to write ppt, very good, in Chinese speaking tutorial things out. The following article is also well written.Http://googlechinablog.com/2006/04/blog-post_17.htmlAn article transferred from the above addressThe beauty of Mathematics series three--application of hidden Markov model in l

Language Processing and Python: 1.1 Text and words

[Preface]Natural Language: the language used for daily communicationNLP: Natural Language ProcessingChapter 4 Language Processing and Python]1.1 la

Qiandu search and language processing lab platform-opening film

From today on, I will officially write some articles about my graduation design system. I was planning to write some articles before, but I always felt that I was missing some knowledge. After more than two months of accumulation, I gradually formed some ideas. During this period, I completed the development of the debug version of the system, accumulated some experience, and learned a lot. I hope my article will inspire you. Overture: More than two months ago, I officially came to my current l

"The beauty of Mathematics", chapter 7th Jarinik and Modern language processing

) was precisely the time when statistical speech recognition and natural language processing began. Two obstacles: a lack of computing power and a large number of computer-readable text corpora that can be used for statistics. The natural language

HANLP-Chinese Language processing package

folding navigation hanlp Download Document Contact About Open Source free Chinese language processing package features full invocation simple Welcome to use HANLPHANLP v1.2.4HANLP is a Java toolkit consisting of a series of models and algorithms that aim to popularize the application of

byte-to-align and its related processing in C language

ShortCC1;//2-byte alignment 011 CharDD1;//1-byte alignment 1} testlength1;intLength1 =sizeof(TESTLENGTH1);//2 byte aligned, takes up bytes one by one 10,length = Tentypedefstruct{ CharBB2;//1-byte alignment 1 intAA2;//2-byte alignment 01111 ShortCC2;//2 byte alignment one CharDD2;//1-byte alignment 1} testlength2;intLength2 =sizeof(TESTLENGTH2);//2 byte aligned, takes up bytes by one by one 10,length = Tentypedefstruct{ CharBb3;//1-byte alignment 1 CharDD3;//1-byte alignment 1 intAa3

[Language Processing and Python] 6.1 supervised classification

Pattern recognition is a core part of natural language processing. 6.1 supervised classification Category: select the correct class tag task for the specified input. Supervised Classification: if the classification is based on the training corpus containing each input correct tag. The framework of supervised classification is as follows: {: Word [-1]} The di

Large data volume, mass data processing method summarizing __c language

there may be a large number of 1001 of the occurrence of aggregation. Therefore, the data can not be randomly divided into different machines, but to be based on the value of the hash to map them to a different machine processing, so that the different computer processing a numerical range. The way you sort it consumes a lot of Io, and it's not efficient. The above distributed method can also be used for s

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