Empirical Comparative Study of Boosting and its Relatives

2013 ◽  
Vol 312 ◽  
pp. 667-672
Author(s):  
Fang Jun Wu
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Transfer Learning ◽  
Research Topic ◽  
Performance Difference ◽  
Important Research ◽  
Knowledge And Skills ◽  
Statistical Framework ◽  
Important Research Topic ◽  
F Measure

Transfer learning is an important research topic in machine learning and data mining that focuses on utilizing knowledge and skills learned in previous tasks to a novel but related task. This paper contributes to comparison between boosting for transfer learning and boosting. The results, in terms of the accuracy, weighted F-Measure, G-Mean, weighted GMPR, weighted precision and weighted AUC, are rigorously tested using the statistical framework proposed by Janez Demsar. Results show that the performance difference between TrAdaBoost and AdaBoost is less significant.

New Information in Trending Topics of Tweets by Labelled Clusters

2015 ◽  
Vol 14 (03) ◽  
pp. 1550019
Author(s):  
Amina Madani ◽  
Omar Boussaid ◽  
Djamel Eddine Zegour
Keyword(s):  
Data Mining ◽  
Real Time ◽  
Exponential Growth ◽  
Research Topic ◽  
Important Research ◽  
New Approach ◽  
New Information ◽  
Important Research Topic ◽  
Trending Topics ◽  
The Web

Twitter is a popular micro-blogging service, and one of the main means of spreading ideas and information throughout the web. In this system, participants post short status messages called tweets that are often available publicly. Recently, the exponential growth of tweets has started to draw the attention of researchers from various disciplines. Numerous research approaches in the data mining field have examined Twitter. How to automatically extract useful information from tweets has therefore become an important research topic. The aim of this paper is to bring up what's up which is a new approach of tweets mining. It is a more general approach that discovers many different trending topics from tweets in real-time. Trending topics have generated big interest not only for the users of Twitter but also for information seekers. Our trending topics are detected for a specific geographic town and compared with the top trending topics shown on Twitter. They are presented by labelled clusters that constitute an accurate description of each trending topic. Each cluster is labelled by an emerging trending topic and is composed of keywords that represent the properties of the trending topic.

Mining Indirect Temporal Sequential Patterns in Large Transaction Databases

2013 ◽  
Vol 385-386 ◽  
pp. 1362-1365
Author(s):  
Wei Min Ouyang ◽  
Qin Hua Huang
Keyword(s):  
Data Mining ◽  
Knowledge Discovery ◽  
Research Topic ◽  
Sequential Pattern ◽  
The Other ◽  
Sequential Patterns ◽  
Important Research ◽  
Data Set ◽  
Important Research Topic ◽  
The One

Sequential pattern is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining sequential patterns focus on the frequent sequences, which do not consider the infrequent sequences and lifespan of each sequence. On the one hand, some infrequent patterns can provide very useful insight view into the data set, on the other hand, without taking lifespan of each sequence into account, not only some discovered patterns may be invalid, but also some useful patterns may not be discovered. So, we extend the sequential patterns to the indirect temporal sequential patterns, and put forward an algorithm to discover indirect temporal sequential patterns in this paper.

Conformal Optimization Algorithm for Undevelopable Surfaces and its Application

2014 ◽  
Vol 602-605 ◽  
pp. 3570-3574
Author(s):  
Zhen Hua Luo ◽  
Fen Jiang
Keyword(s):  
Approximation Algorithms ◽  
Optimization Algorithm ◽  
Manufacturing Process ◽  
Research Topic ◽  
Important Research ◽  
Computer Aided Geometric Design ◽  
Industrial Manufacturing ◽  
Important Research Topic ◽  
Computer Aided ◽  
Planar Materials

In the industrial manufacturing process, most kinds of surfaces are processed by planar materials, but undevelopable surfaces are difficult develop to the plane. The approximation algorithms to develop a undevelopable surface is an important research topic in Computer Aided Geometric Design (CAGD). In this paper, we propose a new approximation algorithms based optimization algorithm. We guarantee the deformation vector make the minimum changes during the developing process. In the paper, some numerical example are given and the can illustrate the our method is effective.

scholarly journals The happy victimizer phenomenon: Not found here

2014 ◽  
Vol 46 (1) ◽  
pp. 145-161
Author(s):  
Ana Jevtic ◽  
Jovan Miric
Keyword(s):  
Emotional Development ◽  
Positive Emotions ◽  
Negative Emotions ◽  
Age Groups ◽  
Research Topic ◽  
Important Research ◽  
Important Research Topic ◽  
Significant Difference ◽  
Moral Explanations

Children?s attribution of emotions to a moral transgressor is an important research topic in the psychology of moral and emotional development. This is especially because of the so-called Happy Victimizer Phenomenon (HVP) where younger children attribute positive emotions to a moral transgressor described in a story. In the two studies that we have conducted (children aged 5, 7 and 9, 20 of each age; 10 of each age in the second study) we have tested the possible influence of the fear of sanctions and the type of transgression (stealing and inflicting body injuries) on the attribution of emotions. Children were presented with stories that described transgressions and they were asked to answer how the transgressor felt. The fear of sanctions did not make a significant difference in attribution but the type of transgression did - more negative emotions were attributed for inflicting body injuries than for stealing. Positive emotions were explained with situational-instrumental explanations in 84% of cases while negative emotions were explained with moral explanations in 63,5%. Girls attributed more positive emotions (61%) than boys (39%). However, our main finding was that, for the aforementioned age groups, we did not find the HVP effect although it has regularly been registered in foreign studies. This finding denies the generalizability of the phenomenon and points to the significance of disciplining styles and, even more so, culture for children?s attribution of emotions to moral transgressors.

scholarly journals Facial Landmark Annotation and Fuzzy Model to Detect Players’ Focus

2021 ◽  
Author(s):  
Alisson Steffens Henrique ◽  
Esteban Walter Gonzalez Clua ◽  
Rodrigo Lyra ◽  
Anita Maria da Rocha Fernandes ◽  
Rudimar Luis Scaranto Dazzi
Keyword(s):  
Fuzzy Model ◽  
Research Topic ◽  
Important Research ◽  
Facial Landmark ◽  
Important Research Topic ◽  
Focus Detection ◽  
Data Log ◽  
Game Analytics

Game Analytics is an important research topic in digitalentertainment. Data log is usually the key to understand players’behavior in a game. However, alpha and beta builds may need aspecial attention to player focus and immersion. In this paper, wepropose t he us e of player’s focus detection, through theclassification of pictures. Results show that pictures can be usedas a new source of data for Game Analytics, feeding developerswith a better understanding of players enjoyment while in testingphases .

scholarly journals Integration of synthetic minority oversampling technique for imbalanced class

2019 ◽  
Vol 13 (1) ◽  
pp. 102
Author(s):  
Noviyanti Santoso ◽  
Wahyu Wibowo ◽  
Hilda Hikmawati
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Support Vector Machine ◽  
Class Imbalance ◽  
Original Data ◽  
Support Vector ◽  
Classification Methods ◽  
Problematic Issue ◽  
Imbalanced Class ◽  
F Measure

In the data mining, a class imbalance is a problematic issue to look for the solutions. It probably because machine learning is constructed by using algorithms with assuming the number of instances in each balanced class, so when using a class imbalance, it is possible that the prediction results are not appropriate. They are solutions offered to solve class imbalance issues, including oversampling, undersampling, and synthetic minority oversampling technique (SMOTE). Both oversampling and undersampling have its disadvantages, so SMOTE is an alternative to overcome it. By integrating SMOTE in the data mining classification method such as Naive Bayes, Support Vector Machine (SVM), and Random Forest (RF) is expected to improve the performance of accuracy. In this research, it was found that the data of SMOTE gave better accuracy than the original data. In addition to the three classification methods used, RF gives the highest average AUC, F-measure, and G-means score.

Trends and Transformations in European Agricultural Economy, Rural Communities and Food Sustainability in Context of New Common Agricultural Policy (CAP) Reforms

2016 ◽  
pp. 1-24
Author(s):  
Andrei Jean-Vasile ◽  
Alexandra Alecu
Keyword(s):  
Rural Communities ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Research Topic ◽  
Economic Sector ◽  
Important Research ◽  
European Level ◽  
Agricultural Economy ◽  
Security Assurance ◽  
Important Research Topic

Agriculture continues to be quite a debate for the last two and a half decades at least at the European level and for Romania Common Agricultural Policy (CAP) reforms has a big impact in developing the convergence to the European agricultural model. Agriculture becomes nowadays a multirole economic sector, with major implications on rural community's sustainability and on food security assurance. In this context, the transformations in European agricultural economy, rural communities and food sustainability in context of Common Agricultural Policy (CAP) reforms represent an important research topic in the context of EU-28 policy diversification from the larger context of Romanian approach.

Deriving Information System Security and Privacy From Value Cocreation Theory

2019 ◽  
Vol 10 (4) ◽  
pp. 1-25
Author(s):  
Christophe Feltus
Keyword(s):  
Information System ◽  
Value Chain ◽  
System Architecture ◽  
Enterprise Architecture ◽  
Research Topic ◽  
Security And Privacy ◽  
Important Research ◽  
Important Research Topic ◽  
Value Cocreation ◽  
The Relationship

Traditionally, the relationship between the company and its providers have for objective to generate value at the company side in exchange of money. This relationship is largely investigated through the vector of value chain. In this article, security and privacy cocreation (SPCC) is investigated as a specialization of value cocreation. Although it is an important research topic, and despite a plethora of research aiming at depicting the fundamental of SPCC, few contributions have been appeared until now in the area of a language to support SPCC design and deployment. However, such a language is necessary to describe elements of the information system, as well as their underlying dependencies. As a result, this article proposes extending an existing enterprise architecture language to support the process of decision-making and to allow understanding and analysis of the impacts associated to a change of the system architecture as a whole.

scholarly journals Vertex-Disjoint Paths in a 3-Ary n-Cube with Faulty Vertices

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Xiaolei Ma ◽  
Shiying Wang
Keyword(s):  
Interconnection Networks ◽  
Transmission Rate ◽  
Research Topic ◽  
Disjoint Paths ◽  
Important Research ◽  
Important Research Topic ◽  
Vertex Disjoint

The construction of vertex-disjoint paths (disjoint paths) is an important research topic in various kinds of interconnection networks, which can improve the transmission rate and reliability. The k-ary n-cube is a family of popular networks. In this paper, we determine that there are m2≤m≤n disjoint paths in 3-ary n-cube covering Qn3−F from S to T (many-to-many) with F≤2n−2m and from s to T (one-to-many) with F≤2n−m−1 where s is in a fault-free cycle of length three.

Nanomaterials and Nanocomposites for Adsorptive Desulfurization

2021 ◽  
pp. 1629-1658
Author(s):  
Saddam A. Al-Hammadi
Keyword(s):  
Research Topic ◽  
Low Energy ◽  
Important Research ◽  
Operation Condition ◽  
Adsorptive Desulfurization ◽  
Important Research Topic ◽  
Low Energy Consumption ◽  
Sulfur Adsorption ◽  
Sulfur Containing ◽  
Sulfur Containing Compounds

Desulfurization (removal of S compounds) of fuels is an important research topic in recent years. Several techniques have been reported to remove the sulfur-containing compounds in fuels. One of these techniques is adsorptive desulfurization (removal based on chemisorption and physisorption), which has received much attention because of low energy consumption and facile operation condition. This chapter discusses the methods employed under this technique and the types of nanocomposites and hybrid materials (adsorbents) that have been investigated as potential adsorbents. The strategies to enhance sulfur adsorption capacity and main challenges will be discussed.

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