A comparison of feature and semantic-based summarization algorithms for Turkish

Akyokuş, Selim (Dogus Author) -- Conference full title: International Symposium on Innovations in Intelligent Systems and Applicaitons, 21-24June 2010, Kayseri & Cappadocia,TURKEY.In this paper we analyze the performances of a feature-based and two semantic-based text summarization algorithms on a new Turkish corpus. The feature-based algorithm uses the statistical analysis of paragraphs, sentences, words and formal clues found in documents, whereas the two semanticbased algorithms employ Latent Semantic Analysis (LSA) approach which enables the selection of the most important sentences in a semantic way. Performance evaluation is conducted by comparing automatically generated summaries with manual summaries generated by a human summarizer. This is the first study that applies LSA based algorithms to Turkish text summarization and its results are promising

Effects of support vector machines parameter optimization on sentiment anaylsis

Güran, Aysun (Dogus Author) -- Uysal, Mitat (Dogus Author)Kişilerin kullandıkları ürünler ve satın aldıkları hizmetler hakkındaki görüşlerini sosyal medya üzerinden paylaşması yorumların kategorize edilmesini sağlayan duygu analizi konusunun önem kazanmasını sağlamıştır. Duygu analizi ile ilgili çalışmalarda sınıflandırma metodu olarak destek vektör makineleri (DVM)’nin başarılı performansı pek çok kez vurgulanmıştır. Bu çalışma ile duygu analizinin gerçekleştirebileceği farklı veri setleri üzerinde DVM yöntem performansını etkileyen parametre değişimlerinin sınıflandırma performansı üzerindeki etkileri incelenmiş ve farklı deneyler sonucu elde edilen durumlar yorumlanmıştır.Sentiment Analysis which has the meaning of categorization of comments has been popular since people share their ideas about the products and services that they bought. The studies about sentiment analysis point out the importance of support vector machines (SVM) many times. By this work, using different sentiment analysis data sets, parameter changes that effects the performance of SVM method have been analysed and different cases that are acquired by different experiments have been interpreted

An efficient algorithm for 3D rectangular box packing

Akyokuş, Selim (Dogus Author) -- Conference full title: 9th International Conference, ETAI 2009, Ohrid, September 26-29, Republic of Macedonia, 2009.Getting highest occupancy rate of capacity of a container is very important for the companies, which deals in shipping or has shipping as a part of their main activities. They have to fit 3D boxes in container with optimum or nearest to optimum placement in order to ship more products with a minimum cost. The problem of fitting the boxes which is different from or the same to each other into a big container in optimum level, is called 3-dimensional packing problem. In this problem, the main objective is to minimize used container volume or wasted container space. This provides the reduction of costs in shipments with the use minimum number of containers

Critical Points in the Management of Pseudohypoaldosteronism Type 1

Pseudohypoaldosteronism type 1 (PHA-1, MIM #264350) is caused by defective transepithelial sodium transport. Affected patients develop life-threatening neonatal-onset salt loss, hyperkalemia, acidosis, and elevated aldosterone levels due to end-organ resistance to aldosterone. In this report, we present a patient diagnosed as PHA-1 who had clinical and laboratory findings compatible with the diagnosis and had genetically proven autosomal recessive PHA-1. The patient received high doses of sodium supplementation and potassium-lowering therapies; however, several difficulties were encountered in the management of this case. The aim of this presentation was to point out the potential pitfalls in the treatment of such patients in the clinical practice and to recommend solutions

SSD efficiency at multiple data frequencies: application on the OECD countries

Güran, Aysun (Dogus Author)The second order stochastic dominance (SSD) has become exceedingly popular in recent years, due to its ability to determine the dominance of one asset over another for all risk-averse investors without a strict requirement in asset distribution. In this study, 33 OECD country indexes and their enriched set of assets, which consists of some combinations of these indexes, are investigated and compared between 2007 and 2015 by utilizing pairwise SSD comparisons, with different data frequencies, such as daily, weekly, monthly and quarterly. This paper contributes to the literature in three points: Firstly, a serious portion of the best performing OECD countries has the lowest GDP (PPP) per capita level. Secondly, the SSD efficient set depends on data frequency. Thirdly, when the data frequency is lowered, the difference between two SSD pairwise efficiency tests decreases

An additive FAHP based sentence score function for text summarization

Güran, Aysun (Dogus Author) -- Uysal, Mitat (Dogus Author)This study proposes a novel additive Fuzzy Analytical Hierarchy Process (FAHP) based sentence score function for Automatic Text Summarization (ATS), which is a method to handle growing amounts of textual data. ATS aims to reduce the size of a text while covering the important points in the text. For this aim, this study uses some sentence features, combines these features by an additive score function using some specific weights and produces a sentence score function. The weights of the features are determined by FAHP - specifically Fuzzy Extend Analysis (FEA), which allows the human involvement in the process, uses pair-wise comparisons, addresses uncertainty and allows a hierarchy composed of main features and sub-features. The sentences are ranked according to their score function values and the highest scored sentences are extracted to create summary documents. Performance evaluation is based on the sentence coverage among the summaries generated by human and the proposed method. In order to see the performance of the proposed system, two different Turkish datasets are used and as a performance measure, the F-measure is used. The proposed method is compared with a heuristic algorithm, namely Genetic Algorithm (GA). Resulting performance improvements show that the proposed model will be useful for both researchers and practitioners working in this research area

Effcient feature integration with Wikipedia-based semantic feature extraction for Turkish text summarization

Abstract: This study presents a novel hybrid Turkish text summarization system that combines structural and semantic features. The system uses 5 structural features, 1 of which is newly proposed and 3 are semantic features whose values are extracted from Turkish Wikipedia links. The features are combined using the weights calculated by 2 novel approaches. The first approach makes use of an analytical hierarchical process, which depends on a series of expert judgments based on pairwise comparisons of the features. The second approach makes use of the artificial bee colony algorithm for automatically determining the weights of the features. To confirm the significance of the proposed hybrid system, its performance is evaluated on a new Turkish corpus that contains 110 documents and 3 human-generated extractive summary corpora. The experimental results show that exploiting all of the features by combining them results in a better performance than exploiting each feature individually

Sentence selection methods for text summarization

Güran, Aysun (Dogus Author) -- Conference full title: 2014 22nd Signal Processing and Communications Applications Conference (SIU) = 2014 22. Sinyal İşleme ve İletişim Uygulamaları Kurultayı (SİU): 23-25 April 2014, Trabzon, Turkey.Bu çalışmanın amacı, bir dokümandaki en önemli cümleleri seçerek ilgili dokümanın özetini çıkarmaktır. Bu amaçla 15 farklı cümle seçim metodu kullanılmıştır. Bu metotlar, 15 kadın ve 15 erkek olmak üzere, toplam 30 kişi tarafından çıkarılmış özet dokümanlarının oluşturduğu bir değerlendirme veri seti üzerinde kıyaslanmıştır. Ayrıca, bu metotlardan en başarılı olanlarının birlikte kullanılması ile elde edilen farklı özellik gruplarının başarım değerleri sergilenmiş ve analiz sonuçları paylaşılmıştır.The aim of this work is to create text summaries by selecting the most important sentences of documents. For this aim 15 sentence selection methods are used. These methods are compared on the evaluation set created by 15 women and 15 men evaluators. The performance results of the systems that are obtained by using different sentence selecetion methods together are also analyzed and the results are shared

NMF based dimension reduction methods for Turkish text clustering

Conference: IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA) -- Location: BULGARIA -- Date: JUN 19-21, 2013In this work, we analyze the effects of NMF based dimension reduction methods on clustering of Turkish documents by using k-means clustering algorithm. All experiments are conducted on two different datasets that we call Milliyet4c1k and 1150haber. The NMF based dimension reduction methods have two purposes: to reduce the original vector space by transformation and to reduce size and dimension by summarizing original documents. Experimental results show that NMF transformation yields to better clustering results on both datasets. Using k-means on summarized documents produces almost identical result with k-means on original documents. Although using summaries instead of full documents doesn't improve quality of clustering, we show that it significantly reduces the size of the processed data and execution time of k-means clustering algorithm.IEEE; Bulgarian Sci Acad; Bulgarian Acad Sci, Inst Informat & Commun Technologies; IEEE Bulgarian Sectio

Unsupervised and supervised term weigthing methods for character n-gram based author categorization

Naiboğlu, H. Selahattin (Dogus Author) -- Kaptıkaçtı, Oğuz (Dogus Author) -- Sardal, E. Cemre (Dogus Author) -- Güran, Aysun (Dogus Author) -- Uysal, Mitat (Dogus Author) -- Conference full title: Joint International Symposium on "The Social Impacts of Developments in Information, Manufacturing and Service Systems" 44th International Conference on Computers and Industrial Engineering, CIE 2014 and 9th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2014; Adile Sultan Palace Istanbul; Turkey; 14 October 2014 through 16 October 2014Author categorization considers the problem of identifying the author of an anonymous article. The goal of this work is to identify authors of articles by using different character n-gram based representations of documents. The use of character n-gram models is a relatively simple idea, but it turns out to be quite effective in many applications. The most important point in n-gram based methods is how to represent the documents. In this study, several widely used unsupervised and supervised n-gram weighting methods are investigated on a Turkish data corpus in combination with different classification algorithms. Apart from this, the character n-gram based features are compared with some stylistic markers and the evaluation results are shared in detail.Computer and Industrial Engineering, Gaziantep University, Istanbul Commercial University, Journal of Intelligent Manufacturing Systems, Sakarya University, Department of Industrial Engineering