Titlebook: Computational Processing of the Portuguese Language; 7th International Wo Renata Vieira,Paulo Quaresma,Maria Carmelita Dias Conference proc

DIS

土坯

Supply Chain Management with SAP APO™e. REPENTINO wishes to minimize the problems developers face due to the limited availability of this type of lexical-semantic resources for Portuguese. The data stored in REPENTINO was mostly extracted from corpora and from the web using simple semi-automated methods. Currently, REPENTINO stores nea

主讲人

换话题

灯泡

Supply Chain Management with SAP APO™peech recognition with the machine translation modules. Transducer inference algorithms to automatically learn the translation module are also presented. Good experimental results confirmed the adequacy of these techniques to limited-domain tasks. In particular, the reordering algorithm proposed sho

施魔法

AMEND

大火

Christopher S. Tang,Kumar Rajaram,Jihong Ou procedure. These rules try to obtain soft matches between candidate entities found in text and instances contained in a wide-scope gazetteer, and avoid the need for coding large sets of rules by exploiting lexical similarities. Using this matching procedure, SIEMÊS generates a set of classification

笨拙的你

Tonya Boone,Ram Ganeshan,Alan J. Stenger term generation and matching in an information retrieval environment. We present tools that automatically perform nominalization for lexical normalization in Portuguese. Comparing the effects of three alternative strategies (stemming, lemmatizing, and our proposal: nominalization), we demonstrate t

Lumbar-Spine

Christopher S. Tang,Kumar Rajaram,Jihong Ouonnected as a chain of filters, apply successive transformations to the data that flows through the system. Hence when integrating such tools, one may face problems that lead to information losses, such as: (i) tools discard information from their input which will be required by other tools further