Developing a keyword extractor and document classifier : emerging research and opportunities / by Dimple Valayil Paul.
"The main problems that prevent fast and high-quality document processing in electronic document management systems are insufficient and unstructured information, information redundancy, and the presence of large amounts of undesirable user information. The human factor has a significant impact...
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| Main Author: | |
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| Format: | Ebook |
| Language: | English |
| Published: |
Hershey, PA :
Information Science Reference,
[2021]
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| Subjects: | |
| Online Access: | IGI Global e-Book Collection |
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| 100 | 1 | |a Paul, Dimple Valayil, |d 1976- |e author. |9 403253 | |
| 245 | 1 | 0 | |a Developing a keyword extractor and document classifier : |b emerging research and opportunities / |c by Dimple Valayil Paul. |
| 264 | 1 | |a Hershey, PA : |b Information Science Reference, |c [2021] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | 0 | |g 1. |t Dynamic Template Generation -- |g 2. |t Grouping of Questions From a Question Bank Using Partition-Based Clustering -- |g 3. |t Question Selection in Template-Based Test Paper Models -- |g 4. |t Syllabus Coverage Evaluation in Test Paper Models -- |g 5. |t Answer Evaluation of Short Descriptive Questions -- |g 6. |t Keyword Extraction -- |g 7. |t Document Classification -- |g 8. |t System Analysis and Design for Document Classification -- |g 9. |t Input Output for Document Classifier -- |g 10. |t Implementation and Testing Details of Document Classification -- |g 11. |t Software Tool for Test Paper Generation. |
| 520 | |a "The main problems that prevent fast and high-quality document processing in electronic document management systems are insufficient and unstructured information, information redundancy, and the presence of large amounts of undesirable user information. The human factor has a significant impact on the efficiency of document search. An average user is not aware of the advanced option of a query language and uses typical queries. Development of a specialized software toolkit intended for information systems and electronic document management systems can be an effective solution of the tasks listed above. Such toolkits should be based on the means and methods of automatic keyword extraction and text classification. The categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years due to the increased availability of documents in digital form and the ensuing need to organize them. Thus, research on keyword extraction, advancements in the field, and possible future solutions is of great importance in current times.Developing a Keyword Extractor and Document Classifier: Emerging Research and Opportunities presents an information extraction mechanism that can process many kinds of inputs, realize the type of text, and understand the percentage of the keywords that has to be stored. This mechanism then supports information extraction and information categorization mechanisms. This module is used to support a text summarization mechanism, which leads—with the help of the keyword extraction module—to text categorization. It employs lexical and information retrieval techniques to extract phrases from the document text that are likely to characterize it and determines the category of the retrieved text to present a summary to the users. This book is ideal for practitioners, stakeholders, researchers, academicians, and students who are interested in the development of a new keyword extractor and document classifier method."--Publisher's website. | ||
| 588 | |a Description based on print version record and CIP data provided by publisher; resource not viewed. | ||
| 650 | 0 | |a Classification |x Technological innovations |9 688860 | |
| 650 | 0 | |a Educational tests and measurements |x Technological innovations |9 688101 | |
| 650 | 0 | |a Examinations |x Design and construction. |9 317612 | |
| 650 | 0 | |a Text data mining. |9 378792 | |
| 776 | 1 | 8 | |w (OCoLC)1151476477 |
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