Given the potentially infinite number of IUPAC entities, it is not feasible to develop a dictionary-based approach to identify them, and natural language processing methods are more suitable to identify those entities.
In 1992, Chowdhury and Lynch [1, 2] developed a dictionary and rule based semiautomatic method to convert chemical texts into structure representation by morphological analysis and dictionary lookup.
This objective has been achieved by developing a dictionary mechanism where many of the semantics are added not through hard-coded elements and attributes but by linking to semantic dictionaries.
Starting with the subset of posts identified to contain AEs, we developed a dictionary to convert Internet vernacular to a standardized regulatory dictionary, namely Medical Dictionary for Regulatory Activities (MedDRA®) version 16 in English.
Liberia received funds to expand the data collection database management and reporting system; Nigeria was funded to advocate to local government authorities and community leaders on the importance of data generation, feedback and use; and Sudan proposed to develop a data dictionary and design a survey for collecting data on the health system's performance.
But bit by bit, he is developing a political dictionary all his own.
In addition, the method used in developing a technology dictionary is presented, employing clustering and network analysis.
This paper develops a Bayesian dictionary learning method for hyperspectral image super resolution in the presence of mixed Poisson Gaussian noise.
Previously, we developed a combined dictionary named Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus [13].
Previously, we developed a combined dictionary dubbed Chemlist for the identification of small molecules and drugs in text based on a number of publicly available databases and tested it on an annotated corpus.
