Zaman anis (64 risultati)

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Taschenbuch. Condizione: Neu. Statistical and Semantic Similarity between English Sentences | Anis Zaman | Taschenbuch | 72 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659616389 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. …

Condizione: New.

Condizione: New.

Condizione: New.

Condizione: New.

PF. Condizione: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents various algorithms to compute semantic similarities between english texts. I explored three different algorithms for computing English sentence similarity. The first algorithm, which is well-explored in the literature [Salton and Buckley, 1988, Wu and Salton, 1981], weights words in each sentence according to term frequency and inverse document frequency (tf-idf ) and uses no semantic information. The second algorithm uses measures of the semantic distance between words belonging to the same part of speech. The third algorithm combines the tf-idf scores and the semantic distance scores between words. I evaluated the performance of the second and third algorithms on two data sets: O'Shea's set of sentence pairs with human similarity judgements [Li et al., Aug, Rubenstein and Goodenough, 1965], and Microsoft Research's sentence-level paraphrase dataset [Rus et al., 2012]. On O'Shea's data set, the third algorithm more accurately matches human judgments than the second. On the Microsoft data set, there was not a significant difference between the two algorithms 72 pp. Englisch.…

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents various algorithms to compute semantic similarities between english texts. I explored three different algorithms for computing English sentence similarity. The first algorithm, which is well-explored in the literature [Salton and Buckley, 1988, Wu and Salton, 1981], weights words in each sentence according to term frequency and inverse document frequency (tf-idf ) and uses no semantic information. The second algorithm uses measures of the semantic distance between words belonging to the same part of speech. The third algorithm combines the tf-idf scores and the semantic distance scores between words. I evaluated the performance of the second and third algorithms on two data sets: O'Shea's set of sentence pairs with human similarity judgements [Li et al., Aug, Rubenstein and Goodenough, 1965], and Microsoft Research's sentence-level paraphrase dataset [Rus et al., 2012]. On O'Shea's data set, the third algorithm more accurately matches human judgments than the second. On the Microsoft data set, there was not a significant difference between the two algorithms.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Zaman AnisAnis Zaman is a Software Engineer living in New York, USA. His works in the Computer Science research space spans from Robotics, Computer Vision to Natural Language Processing. He is also obsessed about the tech industry an.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Spanisch.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents various algorithms to compute semantic similarities between english texts. I explored three different algorithms for computing English sentence similarity. The first algorithm, which is well-explored in the literature [Salton and Buckley, 1988, Wu and Salton, 1981], weights words in each sentence according to term frequency and inverse document frequency (tf-idf ) and uses no semantic information. The second algorithm uses measures of the semantic distance between words belonging to the same part of speech. The third algorithm combines the tf-idf scores and the semantic distance scores between words. I evaluated the performance of the second and third algorithms on two data sets: O¿Sheäs set of sentence pairs with human similarity judgements [Li et al., Aug, Rubenstein and Goodenough, 1965], and Microsoft Research¿s sentence-level paraphrase dataset [Rus et al., 2012]. On O¿Sheäs data set, the third algorithm more accurately matches human judgments than the second. On the Microsoft data set, there was not a significant difference between the two algorithmsVDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Französisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Este libro presenta diversos algoritmos para calcular la similitud semántica entre textos en inglés. He analizado tres algoritmos diferentes para calcular la similitud entre oraciones en inglés. El primer algoritmo, ampliamente estudiado en la bibliografía [Salton y Buckley, 1988; Wu y Salton, 1981], pondera las palabras de cada oración según la frecuencia del término y la frecuencia inversa del documento (tf-idf) y no utiliza información semántica. El segundo algoritmo utiliza medidas de la distancia semántica entre palabras que pertenecen a la misma categoría gramatical. El tercer algoritmo combina las puntuaciones tf-idf y las puntuaciones de distancia semántica entre palabras. Evalué el rendimiento del segundo y el tercer algoritmo en dos conjuntos de datos: el conjunto de pares de oraciones de O'Shea con valoraciones de similitud realizadas por personas [Li et al., Aug, Rubenstein y Goodenough, 1965], y el conjunto de datos de paráfrasis a nivel de oración de Microsoft Research [Rus et al., 2012]. En el conjunto de datos de O'Shea, el tercer algoritmo coincide con mayor precisión con las valoraciones humanas que el segundo. En el conjunto de datos de Microsoft, no se observó una diferencia significativa entre los dos algoritmos.…

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.