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"In essence, Computing with Words (CWW) is a system of computation in which the objects of computation are predominantly words, phrases and propositions drawn from a natural language. CWW is based on fuzzy logic. In science there is a deep-seated tradition of according much more respect to numbers than to words. In a fundamental way, CWW is a challenge to this tradition. What is not widely recognized is that, today, words are used in place of numbers in a wide variety of applications ranging from digital cameras and household appliances to fraud detection systems, biomedical instrumentation and subway trains. CWW offers a unique capability?the capability to precisiate natural language. Unprecisiated (raw) natural language cannot be computed with. A key concept which underlies precisiation of meaning is that of the meaning postulate: A proposition, p, is a restriction on the values which a variable, X?a variable which is implicit in p?is allowed to take.CWW has an important ramification for mathematics. Addition of the formalism of CWW to mathematics empowers mathematics to construct mathematical solutions of computational problems which are stated in a natural language. Traditional mathematics does not have this capability."

"This book constitutes the refereed proceedings of the First CCF Conference, NLPCC 2012, held in Beijing, China, during October/November, 2012. The 43 revised full papers presented were carefully reviewed and selected from 151 submissions. The papers are organized in topical sections on applications on language computing, fundamentals on language computing, machine translation and multi-lingual information access, NLP for search, ads and social networks, question answering and web mining."

"This easy-to-read textbook/reference presents an essential guide to object-oriented C++ programming for scientific computing. With a practical focus on learning by example, the theory is supported by numerous exercises. Features, provides a specific focus on the application of C++ to scientific computing, including parallel computing using MPI, stresses the importance of a clear programming style to minimize the introduction of errors into code, presents a practical introduction to procedural programming in C++, covering variables, flow of control, input and output, pointers, functions, and reference variables, exhibits the efficacy of classes, highlighting the main features of object-orientation, examines more advanced C++ features, such as templates and exceptions."

"A traditional Introduction to Digital Logic course can cover all of Chaps. 1, 2, 3,and 4, selections from Chap. 5, and then all of Chaps. 6, 7, 8, 11, 12, 13, 14, and 17,and maybe selections from Chap. 19. I happen to think Chaps. 15 and 18 are of vitalimportance, and the case study presented in Chap. 20 really ties the whole booktogether, but they are not included in every intro course. What this book adds thatothers in the field leave out, through Chaps. 9, 10, and 16, is more depth forapplications in the computing domain. They can be incorporated in an intro coursegeared towards computer engineers or computer scientists, and I have used thismaterial myself, but they can also benefit these students simply by being in the textas breadth and a good reference for later use even if not directly included in thecourse."

"Ambiguitas adalah masalah yang seringkali ditemui dalam pemrosesan bahasa alami oleh komputer. Word Sense Disambiguation (WSD) adalah upaya untuk menentukan makna yang tepat dari sebuah kata yang ambigu. Berbagai penelitian tentang WSD telah banyak dikerjakan, namun penelitian WSD untuk bahasa Indonesia belum banyak dilakukan. Ketersediaan korpus paralel berbahasa Inggris-Indonesia dan sumber pengetahuan bahasa berupa WordNet bahasa Inggris dan bahasa Indonesia dapat dimanfaatkan untuk menyediakan data pelatihan untuk WSD dengan metode Cross-Lingual WSD (CLWSD). Data pelatihan ini kemudian dijadikan input untuk klasifikasi dengan algoritma Naive Bayes, sehingga model klasifikasinya dapat digunakan untuk melakukan monolingual WSD untuk bahasa Indonesia.Evaluasi klasifikasi menunjukkan rata-rata akurasi hasil klasifikasi lebih tinggi dari baseline. Penelitian ini juga menggunakan stemming dan stopwords removal untuk mengetahui bagaimana efeknya terhadap klasifikasi. Penggunaan stemming menaikkan rata-rata akurasi, sedangkan penerapan stopwords removal menurunkan rata-rata akurasi. Namun pada kata yang memiliki dua makna dalam konteks yang cukup jelas berbeda, stemming dan stopwords removal dapat menaikkan rata-rata akurasi.

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Ambiguity is a problem we frequently face in natural languange processing. Word Sense Disambiguation (WSD) is an attempt to decide the correct sense of an ambiguous word. Various research in WSD have been conducted, but research in WSD for Indonesian Language is still rare to find. The availability of parallel corpora in English and Indonesian language and WordNet for both language can be used to provide training data for WSD with Cross-Lingual WSD (CLWSD) method. This training data can be used as input to the classification process using Naive Bayes classifier.The model resulted by the classification process is then used to do monolingual WSD for Indonesian language. The whole process in this research results in higher accuracy compared to baseline. This research also includes the use of stemming and stopwords removal. The effect of stemming is increasing the average accuracy, whereas stopwords removal is decreasing average accuracy. Nevertheless, for ambiguous words that have distinct context of usage, the use of stemming and stopwords removal can increase average accuracy."

"This book develops a general coarse-to-fine framework for learning and inference in large statistical models for natural language processing.Coarse-to-fine approaches exploit a sequence of models which introduce complexity gradually. At the top of the sequence is a trivial model in which learning and inference are both cheap. Each subsequent model refines the previous one, until a final, full-complexity model is reached. Applications of this framework to syntactic parsing, speech recognition and machine translation are presented, demonstrating the effectiveness of the approach in terms of accuracy and speed. "