A simple semantic kernel approach for SVM using higher-order paths
Üst veriTüm öğe kaydını göster
KünyeAltınel, B., Ganiz, M. C., & Diri, B. (2014). A simple semantic kernel approach for SVM using higher-order paths. In 2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings (pp. 431-435). Piscataway, NJ: IEEE. http://dx.doi.org/10.1109/INISTA.2014.6873656.
The bag of words (BOW) representation of documents is very common in text classification systems. However, the BOW approach ignores the position of the words in the document and more importantly, the semantic relations between the words. In this study, we present a simple semantic kernel for Support Vector Machines (SVM) algorithm. This kernel uses higher-order relations between terms in order to incorporate semantic information into the SVM. This is an easy to implement algorithm which forms a basis for future improvements. We perform a serious of experiments on different well known textual datasets. Experiment results show that classification performance improves over the traditional kernels used in SVM such as linear kernel which is commonly used in text classification.
KaynakIEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
Majority of the existing text classification algorithms are based on the "bag of words" (BOW) approach, in which the documents are represented as weighted occurrence frequencies of individual terms. However, semantic ...
Torunoğlu, Dilara (Doğuş Üniversitesi Fen Bilimleri Enstitüsü, 2013-06)Sentiment classification is one of the important and popular application areas of text classification in which texts are labeled as positive and negative. Moreover, Naive Bayes (NB) is one of the mostly used algorithms in ...
It has been shown that Latent Semantic Indexing (LSI) takes advantage of implicit higher-order (or latent) structure in the association of terms and documents. Higher-order relations in LSI capture "latent semantics". ...