نتایج جستجو برای: Semantic representation
تعداد نتایج: 327613 فیلتر نتایج به سال:
the purpose of this study was twofold: (a) to assess the retention of two word types (synonyms and homonyms) in the short term memory, and (b) to investigate the effect of these word types on word learning by asking learners to learn their persian meanings. a total of 73 iranian language learners studying english translation participated in the study. for the first purpose, 36 freshmen from an ...
Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...
schema matching is a critical step in many applications, such as data warehouse loading, online analytical process (olap), data mining, semantic web [2] and schema integration. this task is defined for finding the semantic correspondences between elements of two schemas. recently, schema matching has found considerable interest in both research and practice. in this paper, we present a new impr...
Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...
this paper examines the semantic contribution of -?r and -andeh suffixes in persian based on lieber’s (2004) lexical semantic representation. this framework using six semantic features ([material], [dynamic], [location], [ieps] , [b] and [ci] and a principle called coordination principle studies the semantic contribution of lexical items including affixes and their functions in compounding, der...
Named entities recognition is a fundamental task in the field of natural language processing. It is also known as a subset of information extraction. The process of recognizing named entities aims at finding proper nouns in the text and classifying them into predetermined classes such as names of people, organizations, and places. In this paper, we propose a named entity recognizer which benefi...
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
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