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"This book focusing on the formation, distribution and semantic interpretation of quantificational expressions, the book explores 17 languages including German, Italian, Russian, Mandarin Chinese, Malagasy, Hebrew, Pima, Basque, and more. The language data sets enable detailed crosslinguistic comparison of numerous features. These include semantic classes of quantifiers (generalized existential, generalized universal, proportional, partitive), syntactically complex quantifiers (intensive modification, Boolean compounding, exception phrases) and several others such as quantifier scope ambiguities, quantifier float, and binary quantifiers. "

"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. "

"Penelitian ini membahas tentang pengembangan sistem Chatbot pada customer service bengkel motor dengan menggunakan algoritma cosine similarity. Cosine Similarity merupakan algoritma dengan basis dua vektor yang dihitung persamaannya berdasarkan sudut kedua vektor tersebut untuk mengukur tingkat kemiripan teks. Masukan sistem berupa percakapan teks yang pada proses selanjutnya diubah menjadi vektor dengan besar nilai vektor mengikuti dataset yang ada menggunakan metode Bag Of Words dengan dataset untuk membalas percakapan tersebut. Kemiripan suatu teks menggunakan akurasi dari perhitungan cosine similarity dengan akurasi sebesar 82.7%. Diamati faktor-faktor yang mempengaruhi akurasi setiap pengguna. Dalam penelitian ini, sistem menggunakan dataset sebesar 472 data katalog sepeda motor.

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This paper discusses the development of a chatbot system in a motorcycle garage using the cosine similarity algorithm. Cosine similarity is an algorithm to calculate the degree of similarity of two vectors based on the value of the angle between the two vectors. The chatbot receives an input consisting of a sentence which is then converted into a vector using the Bag of Words algorithm. Using the cosine similarity algorithm, an accuracy of 82.7% is achieved. This paper utilizes 472 motorcycle catalogues as a dataset to perform the calculation and prediction previously mentioned."