A subject identification method based on term frequency technique
| Autor: | Aniza Mohamed Din, Ku Ruhana Ku-Mahamud, Nurul Syafidah Jamil, Faudziah Ahmad, Roshidi Din, Wan Hussain Wan Ishak, Farzana Kabir Ahmad, Noraziah Che Pa |
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| Rok vydání: | 2017 |
| Předmět: |
Information retrieval
General Computer Science business.industry Computer science Process (engineering) Specific-information media_common.quotation_subject Subject (documents) Semantics Term (time) Identification (information) Text mining Reading (process) ComputingMethodologies_DOCUMENTANDTEXTPROCESSING Electrical and Electronic Engineering business media_common |
| Zdroj: | International Journal of Advanced Computer Research. 7:103-110 |
| ISSN: | 2277-7970 2249-7277 |
| DOI: | 10.19101/ijacr.2017.730020 |
| Popis: | The analyzing and extracting important information from a text document is crucial and has produced interest in the area of text mining and information retrieval. This process is used in order to notice particularly in the text. Furthermore, on view of the readers that people tend to read almost everything in text documents to find some specific information. However, reading a text document consumes time to complete and additional time to extract information. Thus, classifying text to a subject can guide a person to find relevant information. In this paper, a subject identification method which is based on term frequency to categorize groups of text into a particular subject is proposed. Since term frequency tends to ignore the semantics of a document, the term extraction algorithm is introduced for improving the result of the extracted relevant terms from the text. The evaluation of the extracted terms has shown that the proposed method is exceeded other extraction techniques. |
| Databáze: | OpenAIRE |
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