Indices of novelty for emerging topic detection
► We develop a new set of indices for emerging topic detection. ► The novelty index (NI) is created based on time. ► The published volume index (PVI) is designed based on frequency. ► They are utilized to determine the detection point (DP) and worthiness of topics. ► The algorithms can decide the no...
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| Published in | Information processing & management Vol. 48; no. 2; pp. 303 - 325 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.03.2012
Elsevier Elsevier Science Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0306-4573 1873-5371 |
| DOI | 10.1016/j.ipm.2011.07.006 |
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| Abstract | ► We develop a new set of indices for emerging topic detection. ► The novelty index (NI) is created based on time. ► The published volume index (PVI) is designed based on frequency. ► They are utilized to determine the detection point (DP) and worthiness of topics. ► The algorithms can decide the novelty and life span of emerging topics.
Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. |
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| AbstractList | Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. Adapted from the source document. Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. [PUBLICATION ABSTRACT] Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. ► We develop a new set of indices for emerging topic detection. ► The novelty index (NI) is created based on time. ► The published volume index (PVI) is designed based on frequency. ► They are utilized to determine the detection point (DP) and worthiness of topics. ► The algorithms can decide the novelty and life span of emerging topics. Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The current methods of text mining and data mining used for this purpose focus only on the frequency of which subjects are mentioned, and ignore the novelty of the subject which is also critical, but beyond the scope of a frequency study. This work tackles this inadequacy to propose a new set of indices for emerging topic detection. They are the novelty index (NI) and the published volume index (PVI). This new set of indices is created based on time, volume, frequency and represents a resolution to provide a more precise set of prediction indices. They are then utilized to determine the detection point (DP) of new emerging topics. Following the detection point, the intersection decides the worth of a new topic. The algorithms presented in this paper can be used to decide the novelty and life span of an emerging topic in a specific field. The entire comprehensive collection of the ACM Digital Library is examined in the experiments. The application of the NI and PVI gives a promising indication of emerging topics in conferences and journals. |
| Author | Seng, Jia-Lang Tu, Yi-Ning |
| Author_xml | – sequence: 1 givenname: Yi-Ning surname: Tu fullname: Tu, Yi-Ning email: 082435@mail.fju.edu.tw organization: Department and Graduate School of Statistics and Information Science, College of Management, Fu Jen Catholic University, New Taipei 242, Taiwan – sequence: 2 givenname: Jia-Lang surname: Seng fullname: Seng, Jia-Lang email: seng@nccu.edu.tw organization: Department and Graduate School of Accounting, College of Commerce, National Chengchi University, Taipei 116, Taiwan |
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| Keywords | Text mining Aging theory Topic detection and tracking Information retrieval Published volume index Novelty index Volume Ageing Index (documentation) |
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| Snippet | ► We develop a new set of indices for emerging topic detection. ► The novelty index (NI) is created based on time. ► The published volume index (PVI) is... Emerging topic detection is a vital research area for researchers and scholars interested in searching for and tracking new research trends and topics. The... |
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| SubjectTerms | Aging theory Algorithms Automatic text analysis Collection Conferences Data mining Data processing Digital libraries Digital systems Exact sciences and technology Information and communication sciences Information processing and retrieval Information retrieval Information retrieval systems. Information and document management system Information retrieval. Man machine relationship Information science. Documentation Life span Methods Novelty index Published volume index Research process. Evaluation Sciences and techniques of general use Studies Subject fields Text mining Texts Topic detection and tracking Tracking |
| Title | Indices of novelty for emerging topic detection |
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