"topic identification" is a correct and usable phrase in written English.
You can use it to refer to the process of determining the main idea of a document or text. For example, "Before I can begin my research paper, I need to complete the topic identification process to determine my exact focus."
The topic identification algorithm's performance becomes doubtful in various cases.
For the task of topic identification our experiments show a relative reduction in topic identification error of 44.94% when compared to the baseline method, the Generalized Vector Model with a classic TF IDF weighting scheme.
These techniques include text segmentation, summary extraction, feature selection, term association, cluster generation, topic identification, and information mapping.
These cases are explored and the reasons underlying the inconsistent performance of automatic topic identification are investigated with statistical analysis and experimental design techniques.
In addition, the threshold value of the output level of neural networks is the most influential parameter on the performance of new topic identification.
The objective of the study is to determine the best set of parameters for neural networks that are designed to perform automatic new topic identification.
The topic or issue identification stage covers the generation of the original ideas for the research.
The main study objectives are: 1) to set up interventions promoting patient involvement in these regions in the selection of HTA topics (identification and prioritization) and in the development of the assessment plan of the chosen subject, and 2) to assess the impacts of these interventions from the point of view of patients and other groups involved in HTA.
Evaluation of the system for topic recognition and entity identification is conducted on a gold standard corpus of annotated news articles.
The article provides a literature review on the topic of identification of supply and demand.
Our study adds to previous research on this topic the identification of three clusters of countries that are homogeneous regarding the variation in prostate cancer mortality, as well the trends in MI ratios, while remaining heterogeneous regarding the distribution of variables traditionally used for an a priori grouping of the countries, namely geographical region and GNI per capita.
