scholarly journals Research on the Relationship between Human Resource Management Activities and Enterprise Performance Based on the Supervised Learning Model

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Chan Sun ◽  
Xiaojuan Li
Keyword(s):  
Text Classification ◽  
Feature Space ◽  
Information Support ◽  
Enterprise Performance ◽  
Job Seekers ◽  
Accuracy Rate ◽  
Job Opportunities ◽  
Rich Information ◽  
The Relationship

HRMS is a very critical tool for companies. The recruitment text contains rich information that can provide strong information support for the company’s recruitment work and also improve the efficiency of job seekers in finding job opportunities. To this end, for the problem of multilabel text classification of recruitment information, this paper provides two algorithms for multilayer classification based on supported SVM. First, the same learning subclass method is used for text sorting subclass acquisition, and then, the class of the text is determined. Second, the hemispherical support SVM is used to find the smallest hypersphere in the feature space that contains the most text of that class and segment the text of that class from other texts. For the text to be classified, the distance from it to the center of each hypersphere is used to determine the class of the text. Experimental results on recruitment data demonstrate that the algorithm in this paper has a high check-all rate, check-accuracy rate, and F1. And, the relationship between HRM activities and corporate performance is discussed.

scholarly journals Reducing the Deterioration of Sentiment Analysis Results Due to the Time Impact

Information ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 184 ◽  
Author(s):  
Yuliya Rubtsova
Keyword(s):  
Computational Complexity ◽  
Text Classification ◽  
Feature Space ◽  
Sentiment Classification ◽  
Text Collections ◽  
Word Representation ◽  
F Measure ◽  
Over Time

The research identifies and substantiates the problem of quality deterioration in the sentiment classification of text collections identical in composition and characteristics, but staggered over time. It is shown that the quality of sentiment classification can drop up to 15% in terms of the F-measure over a year and a half. This paper presents three different approaches to improving text classification by sentiment in continuously-updated text collections in Russian: using a weighing scheme with linear computational complexity, adding lexicons of emotional vocabulary to the feature space and distributed word representation. All methods are compared, and it is shown which method is most applicable in certain cases. Experiments comparing the methods on sufficiently representative text collections are described. It is shown that suggested approaches could reduce the deterioration of sentiment classification results for collections staggered over time.

scholarly journals Political Connections and Enterprise Performance of Private Enterprises in China: Impacts and Mechanisms

2020 ◽  
Vol 12 (10) ◽  
pp. 86
Author(s):  
Yang Wen ◽  
Guo Feng
Keyword(s):  
Political Connections ◽  
Enterprise Performance ◽  
Political Connection ◽  
Internal Governance ◽  
Mediating Role ◽  
Marginal Contributions ◽  
Enterprise Survey ◽  
The Impact ◽  
The Relationship

Researchers have not come to an agreement on the impact of political connection on enterprise performance although this issue draws much attention. This paper attributes the above phenomenon to lack of precise classification of various political connection types in China. Based on existing literature, this paper divides political connections into current political connections and former political connections, and identifies their own hierarchy. Empirical study using Chinese Private Enterprise Survey data shows that different sorts of political connections all contribute to enterprise performance, and internal governance plays the mediating role. Overall, this paper may make marginal contributions to the study on the relationship between political connections and enterprise performance.

scholarly journals Klasifikasi Penentuan Jenis Obat Menggunakan Algoritma Decision Tree

2021 ◽  
Vol 7 (3) ◽  
pp. 53-60
Author(s):  
Rika Nursyahfitri ◽  
Alfanda Novebrian Maharadja ◽  
Riva Arsyad Farissa ◽  
Yuyun Umaidah
Keyword(s):  
Decision Tree ◽  
Medical Records ◽  
Training Data ◽  
Accuracy Rate ◽  
Data Set ◽  
Drug Determination ◽  
Decision Tree Method ◽  
The Relationship ◽  
Tree Method

Classification is a technique that can be used for prediction, where the predicted value is a label. The classification of drug determination aims to predict the type of drug that is accurate for patients with the dataset that has been obtained. The data used in this study are data from the patient's medical records based on the symptoms of the disease but the type of medicine is not yet known. The data set used comes from kaggle.com which is then presented in the form of a decision tree with a mathematical model. To complete this research, a classification method is used in data mining, namely the decision tree. The decision tree method is used to find the relationship between a number of candidate variables, so that it becomes a classification target variable by dividing the data into 70% data testing and 30% training data. The results obtained from this study are in the form of rules and an accuracy rate of 96.36% as well as the recall and precision values ​​of each type of drug using a multiclass configuration matrix.

scholarly journals UTILIZAÇÃO PRÁTICA DE WORD EMBEDDING APLICADA À CLASSIFICAÇÃO DE TEXTO

2020 ◽  
Author(s):  
Luiz Fernando Spillere de Souza ◽  
Alexandre Leopoldo Gonçalves
Keyword(s):  
Text Classification ◽  
Word Embedding ◽  
Practical Application ◽  
Accuracy Rate ◽  
Unstructured Text ◽  
Representation Technique ◽  
Concept Of Word

Text classification aims to extract knowledge from unstructured text patterns. The concept of word incorporation is a representation technique that allows words with similar meanings to have a similar representation, in order to incorporate reasoning characteristics about their use and meaning. The aim of this article is to analyze the work already published on the use of embedded words applied to the classification of texts, to propose a practical application that demonstrates its effectiveness. This study contributes to proving the effectiveness of the use of word incorporation applied to text classification, having reached an accuracy rate of around 73%.

scholarly journals Applications of Deep Learning in News Text Classification

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Menghan Zhang
Keyword(s):  
Deep Learning ◽  
Text Classification ◽  
Recall Rate ◽  
Technological Advancement ◽  
Text Data ◽  
Healthcare Data ◽  
Feature Information ◽  
And Performance ◽  
The Relationship

The advancement in technology is taking place with an accelerating pace across the globe. With the increasing expansion and technological advancement, a vast volume of text data are generated everyday, in the form of social media platform, websites, company data, healthcare data, and news. Indeed, it is a difficult task to extract intriguing patterns from the text data, such as opinions, summaries, and facts, having varying length. Because of the problems of the length of text data and the difficulty of feature value extraction in news, this paper proposes a news text classification method based on the combination of deep learning (DL) algorithms. In order to classify the text data, the earlier approaches use a single word vector to express text information and only the information of the relationship between words were considered, but the relationship between words and categories was ignored which indeed is an important factor for the classification of news text. This paper follows the idea of a customized algorithm which is the combination of DL algorithms such as CNN, LSTM, and MLP and proposes a customized DCLSTM-MLP model for the classification of news text data. The proposed model is expressed in parallel with word vector and word dispersion. The relationship among words is represented by the word vector as an input of the CNN module, and the relationship between words and categories is represented by a discrete vector as an input of the MLP module in order to realize comprehensive learning of spatial feature information, time-series feature information, and relationship between words and categories of news text. To check the stability and performance of the proposed method, multiple experiments were performed. The experimental results showed that the proposed method solves the problems of text length, difficulty of feature extraction in the news text, and classification of news text in an effective way and attained better accuracy, recall rate, and comprehensive value as compared to the other models.

K-MEANS CLUSTERING ALGORITHM BASED CLASSIFICATION OF SOIL FERTILITY IN NORTH WEST NIGERIA

2020 ◽  
Vol 4 (2) ◽  
pp. 780-787
Author(s):  
Ibrahim Hassan Hayatu ◽  
Abdullahi Mohammed ◽  
Barroon Ahmad Isma’eel ◽  
Sahabi Yusuf Ali
Keyword(s):  
Soil Fertility ◽  
Crop Yield ◽  
Clustering Algorithm ◽  
Soil Samples ◽  
North West ◽  
R Programming ◽  
Available Information ◽  
Northwest Region ◽  
The Relationship

Soil fertility determines a plant's development process that guarantees food sufficiency and the security of lives and properties through bumper harvests. The fertility of soil varies according to regions, thereby determining the type of crops to be planted. However, there is no repository or any source of information about the fertility of the soil in any region in Nigeria especially the Northwest of the country. The only available information is soil samples with their attributes which gives little or no information to the average farmer. This has affected crop yield in all the regions, more particularly the Northwest region, thus resulting in lower food production.  Therefore, this study is aimed at classifying soil data based on their fertility in the Northwest region of Nigeria using R programming. Data were obtained from the department of soil science from Ahmadu Bello University, Zaria. The data contain 400 soil samples containing 13 attributes. The relationship between soil attributes was observed based on the data. K-means clustering algorithm was employed in analyzing soil fertility clusters. Four clusters were identified with cluster 1 having the highest fertility, followed by 2 and the fertility decreases with an increasing number of clusters. The identification of the most fertile clusters will guide farmers on where best to concentrate on when planting their crops in order to improve productivity and crop yield.

The innovative space as the most important element of theregional socio-economic space

2019 ◽  
pp. 60-70
Author(s):  
Larysa Gromozdova ◽  
Inna Stenicheva
Keyword(s):  
Basic Element ◽  
Information Support ◽  
Space Region ◽  
Regional Innovation ◽  
Economic Space ◽  
Mechanisms Of Formation ◽  
Innovation Space ◽  
Space Mechanisms ◽  
Constituent Elements

Purpose of the article: to determine the essence of different elements ofsocio-economic space of the region. Construction of the structure and isolationof individual elements of socio-economic space as a multi-vector formation.This article highlights the essence and different approaches to defining theconcepts, structure and mechanisms of formation of economic and social spacesof the region, innovation space as a basic element of socio-economic space.Research Methods: The methodological basis of the research is the fundamentalprinciples of economic theory, regional economy, scientific views and approachesof foreign and domestic scientists. To achieve the purpose of the study, themethods used at the empirical and theoretical levels were used: axiomatic,abstract, system-structural analysis, analogies and comparisons, graphoanalytic,by which the characterization of the nature of the concepts of space, socioeconomic space, as well as innovation space region. Their general properties,structure and functions are described.The criteria of optimality and balancesof interests in the formation of different types of space in the region areconsidered. The classification of the regional space is proposed, and the networkconnections of the innovation space according to components and elements arerevealed, which allows to study deeply the social, economic and other problemsof development of the region.Scientific novelty: the classification of regionalspace by separate constituent elements is proposed. The concept of “innovationspace” was introduced into scientific circulation, the scheme of networkconnections of the innovation space with other elements of the regional socioeconomic space was developed. Conclusions and Prospects for Further Research:In today’s context, it is possible to significantly improve the economic stateof development of Ukrainian regions by using a scientifically sound andcomprehensive approach to defining and studying the concepts of socioeconomic and innovative space.In the further study it is necessary to considerin detail the mechanism of organizational activity of innovation space in theregion. It is very important to pay attention to information support for theformation of the innovation space, the creation of a regional legal field ofinnovation space, mechanisms for coordinating regional innovation activitieswithin the innovation space, as well as the influence of internal and externalfactors on the formation and development of the innovation space.

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

DONG SON BRONZE DRUM - THE WORK OF THE LAC VIET PEOPLE

2018 ◽  
Author(s):  
Nguyen Van Hao
Keyword(s):  
Classification Criteria ◽  
Way Of Life ◽  
Tribal Identity ◽  
The Relationship

Bronze drums are widely distributed, broader than the range of a nation. Therefore, the identification of each kind of drum is a basic subject, should be concerned. In determining the tribal identity of the drum, the classification of drum is the key stage, the relationship between the objective of the classification and classification criteria is the relation as shape and shadow, if there is no right criteria then the result of division will be difficult to reach the desired goal. Likewise, the criterion of the pattern on the bronze drum brought to the affirmation is the Dong Son bronze drum of the Lac Viet people. And the parallel is the affirmation of the culture, way of life, residence of the nation created the drum.

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