Ensemble classification over stock market time series and economy news

Şeker, Şadi Evren; Mert, Cihan; Al-Naami, Khaled; Ayan, Uğur; Ozalp, Nuri

doi:10.1109/isi.2013.6578840

Cited by 15 publications

(7 citation statements)

References 3 publications

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“…TSC is subject to intensive research since its applicability to a plethora of domains, reaching from machine failure detection in an industrial setting [13] to stock market data [14] or speech recognition [15]. Hence, manifold approaches to TSC exist, each with their own up-and downsides.…”

Section: Time Series Classificationmentioning

confidence: 99%

A time series classification approach to non-destructive hardness testing using magnetic Barkhausen noise emission

Unterberg

Stanke

Trauth

et al. 2021

Prod. Eng. Res. Devel.

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The process setup of manufacturing processes is generally knowledge-based and carried out once for a material batch. Industry experts observe fluctuations in product quality and tool life, albeit the process setup remains unchanged. These fluctuations are mainly attributed to fluctuations in material parameters. An in-situ detection of changes in material parameters would enable manufacturers to adapt process parameters like forces or lubrication before turbulences like unexpectedly high tool wear or degradation in product quality occurs. This contribution shows the applicability of a deep learning time series classification architecture that does not rely on handcrafted feature engineering for the classification of hardness fluctuations in a sheet-metal coil using magnetic Barkhausen noise emission. This methodology is not limited to the detection of hardness fluctuations in sheet-metal coils and can potentially be applied for the in-situ material property classification in different manufacturing processes and for different material parameters.

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Section: Time Series Classificationmentioning

confidence: 99%

A time series classification approach to non-destructive hardness testing using magnetic Barkhausen noise emission

Unterberg

Stanke

Trauth

et al. 2021

Prod. Eng. Res. Devel.

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“…We have applied the ensemble classification [11] over the classification algorithms KNN, SVM and ANN where they run over the feature vectors to classify the texts between authors.…”

Section: B Executionmentioning

confidence: 99%

A Novel String Distance Function Based on Most Frequent K Characters

Şeker¹,

Altun²,

Ayan³

et al. 2014

IJMLC

Self Cite

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Abstract-This study aims to publish a novel similarity metric to increase the speed of comparison operations. Also the new metric is suitable for distance-based operations among strings.Most of the simple calculation methods, such as string length are fast to calculate but doesn't represent the string correctly. On the other hand the methods like keeping the histogram over all characters in the string are slower but good to represent the string characteristics in some areas, like natural language.We propose a new metric, easy to calculate and satisfactory for string comparison.Method is built on a hash function, which gets a string at any size and outputs the most frequent K characters with their frequencies.The outputs are open for comparison and our studies showed that the success rate is quite satisfactory for the text mining operations.

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“…Turkey has a high competitive market and in a special XU30 index, which is keeping the most prestigious 30 companies in Turkey, there are 7 banks [6]- [8] and all the banks are offering the insurance service. The similar case applies for most of the markets like European or US markets.…”

Section: Background and Motivationmentioning

confidence: 99%

Human Resource Management Problems for Insurance Company Mergers: A Case Study

Okur¹,

Dilbaz²,

Şeker³

2014

JOAMS

Self Cite

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In this study, we have studied a case of two leading insurance company merger, which are Aviva and Ak insurance companies operating in Turkey. The company merger case is studied according to the human resource management (HRM) approach. During the study, the HRM perspective of merger is based on the interviews by C-level executives and many HRM related outputs, like gender, age or education level statistics are collected from the company merger. The case, studied in this research, is the biggest merger in Turkish insurance sector up until now and the outputs first time published in this paper states a useful base line for further studies. In this paper, the qualitative outcomes of merger, like the number of employees, education levels or the gender and age distribution is published as well as the qualitative outputs like the strategic achievements, organizational commitment or the leadership model. Another important section is holding the steps followed by the HRM department after the merger operation. 

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Ensemble classification over stock market time series and economy news

Cited by 15 publications

References 3 publications

A time series classification approach to non-destructive hardness testing using magnetic Barkhausen noise emission

A time series classification approach to non-destructive hardness testing using magnetic Barkhausen noise emission

A Novel String Distance Function Based on Most Frequent K Characters

Human Resource Management Problems for Insurance Company Mergers: A Case Study

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