Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Zafer Erenel"'
Publikováno v:
Applied Sciences, Vol 10, Iss 15, p 5351 (2020)
This paper presents a new scheme for term selection in the field of emotion recognition from text. The proposed framework is based on utilizing moderately frequent terms during term selection. More specifically, all terms are evaluated by considering
Externí odkaz:
https://doaj.org/article/b76d3b3707694df592762f3b8a2ddec0
Publikováno v:
Applied Sciences, Vol 10, Iss 5351, p 5351 (2020)
Applied Sciences
Volume 10
Issue 15
Applied Sciences
Volume 10
Issue 15
This paper presents a new scheme for term selection in the field of emotion recognition from text. The proposed framework is based on utilizing moderately frequent terms during term selection. More specifically, all terms are evaluated by considering
Autor:
Hakan Altınçay, Zafer Erenel
Publikováno v:
Applied Intelligence. 41:310-326
A novel framework for termset based feature extraction is proposed for binary text classification. The proposed approach is based on the encoding of the terms within a termset. The ternary codes `+1' and `−1' are used to represent the class that th
Autor:
Zafer Erenel, Hakan Altınçay
Publikováno v:
Pattern Recognition Letters. 34:1372-1380
In nearest feature line approach, the representational capacity of a given training set is generalized by defining feature lines passing through each pair of samples belonging to the same class. This technique is shown to provide superior performance
Autor:
Hakan Altınçay, Zafer Erenel
Publikováno v:
Engineering Applications of Artificial Intelligence. 25:1505-1514
In automatic text categorization, the influence of features on the decision is set by the term weights which are conventionally computed as the product of term frequency and collection frequency factors. The raw form of term frequencies or their loga
Autor:
Hakan Altınçay, Zafer Erenel
Publikováno v:
Applied Intelligence. 36:148-160
In this study, the differences among widely used weighting schemes are studied by means of ordering terms according to their discriminative abilities using a recently developed framework which expresses term weights in terms of the ratio and absolute
Autor:
Zafer Erenel, Hakan Altınçay
Publikováno v:
Pattern Recognition Letters. 31:1310-1323
An analytical evaluation of six widely used term weighting techniques for text categorization is presented. The analysis depends on expressing the term weights using term occurrence probabilities in positive and negative categories. The weighting beh
Autor:
Hakan Altınçay, Zafer Erenel
The distribution of documents over two classes in binary text categorization problem is generally uneven where resampling approaches are shown to improve F 1 scores. The improvement achieved is mainly due to the gain in recall where precision may det
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d12128534f74db4e3b9663931a5371e4
https://aperta.ulakbim.gov.tr/record/109227
https://aperta.ulakbim.gov.tr/record/109227
Publikováno v:
2009 Fifth International Conference on Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control.
Term weighting schemes used in text categorization can be considered as functions of term occurence probabilities in positive and negative classes. In this paper, widely used weighting schemes are firstly evaluated from this perspective. Then, a nove