Results 211 to 220 of about 8,969 (257)

A study of supervised term weighting scheme for sentiment analysis

Expert Systems With Applications, 2014
Term weighting is a strategy that assigns weights to terms to improve the performance of sentiment analysis and other text mining tasks. In this paper, we propose a supervised term weighting scheme based on two basic factors: Importance of a term in a ...
Zhi-Hong Deng
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Feature Selection and Term Weighting

2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014
Term-based approaches can extract many features in text documents, but most include noise. Many popular text-mining techniques have been adapted to reduce noisy information from extracted features but still contains some noises features. However, the noise features are extracted from the same training documents that good features extracted from ...
Abdulmohsen Algarni, Nasser Tairan
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Relevance weighting of search terms

Journal of the American Society for Information Science, 1976
AbstractThis paper examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general.
Stephen E. Robertson, Karen Spärck Jones   +1 more
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A New Term Significance Weighting Approach

Journal of Intelligent Information Systems, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jin Zhang 0010, Tien Nhut Nguyen
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Term Birth Weight and Neurodevelopmental Outcomes

Epidemiology, 2021
Background: Preterm birth is an important risk factor for neurodevelopmental disabilities. The vast majority of these disabilities occur, however, among term births. The role of fetal growth restriction specifically among term babies has been incompletely described.
Marianna, Cortese, Dag, Moster, Allen J, Wilcox   +2 more
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Index term weighting

Information Storage and Retrieval, 1973
Abstract Various approaches to index term weighting have been investigated. In particular, claims have been made for the value of statistically-based indexing in automatic retrieval systems. The paper discusses the logic of different types of weighting, and describes experiments testing weighting schemes of these types. The results show that one type
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Modified frequency-based term weighting schemes for text classification

Applied Soft Computing Journal, 2017
With the rapid growth of textual content on the Internet, automatic text categorization is a comparatively more effective solution in information organization and knowledge management.
Thabit Sabbah, Ali Selamat, Fawaz S Al-Anzi   +2 more
exaly   +2 more sources

Domain Relevance on Term Weighting

2007
The TFxIDF term weighting scheme is the standard approach on vectorization of textual data. For a data set where textual data stemming from web document structure is to be vectorized [2] the need for a enhanced term weighting scheme arose. In this publication we introduce a term weighting scheme which improves the behavior compared to the traditional ...
Marko Brunzel, Myra Spiliopoulou
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Refining term weights of documents using term dependencies

Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, 2004
When processing raw documents in Information Retrieval (IR) System, a term-weighting scheme is used to calculate the importance of each term which occurs in a document. However, most term-weighting schemes assume that a term is independent of the other terms. Term dependency is an indispensable consequence of language use [1].
Hee-Soo Kim, Ikkyu Choi, Minkoo Kim
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Supervised term weighting for sentiment analysis

Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, 2011
Vector space text classification is commonly used in intelligence applications such as email and conversation analysis. In this paper we propose a supervised term weighting scheme called tƒ × KL (term frequency Kullback-Leibler), which weights each word proportionally to the ratio of its document frequency across the positive and negative class.
Tam T. Nguyen, Kuiyu Chang, Siu Cheung Hui   +2 more
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