发布求助
文献互助 智能选刊 最新文献

Int. J. Knowl. Eng. Data Min.最新文献

筛选
英文 中文
Combining decision trees classifiers: a case study of automatic sleep stage scoring 结合决策树分类器:睡眠阶段自动评分的案例研究
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2012.044707
N. Khasawneh, Stefan Conrad, L. Fraiwan, E. Taqieddin, B. Khasawneh
{"title":"Combining decision trees classifiers: a case study of automatic sleep stage scoring","authors":"N. Khasawneh, Stefan Conrad, L. Fraiwan, E. Taqieddin, B. Khasawneh","doi":"10.1504/IJKEDM.2012.044707","DOIUrl":"https://doi.org/10.1504/IJKEDM.2012.044707","url":null,"abstract":"This paper presents a new approach of classification in which multiple decision trees are combined together for achieving better accuracy compared to that achieved by each of the individual constituent decision trees. A major unit of the proposed system is the combination unit for which we present two algorithms; one is based on pre-pruning and true positive rate and the other is based on maximum probability voting. In presenting this new method, we use the case study of sleep stage scoring as a basis of demonstration. For such a task, two tree classifications are utilised. We performed a tree classification based on the training data and then combined the resulting model with another classification tree supplemented by the expert according to Rechtschaffen and Kale's sleep scoring rules. We applied this method to nine recordings, six of which were used to construct the training tree and the remaining three were used for testing. The experiments showed that the combination method has a 7% better accuracy over a single model.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115476703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Fuzzy logic-based framework for measuring strength of sentiments in web data 基于模糊逻辑的web数据情感强度度量框架
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2017.10010630
Anil Kumar
{"title":"Fuzzy logic-based framework for measuring strength of sentiments in web data","authors":"Anil Kumar","doi":"10.1504/IJKEDM.2017.10010630","DOIUrl":"https://doi.org/10.1504/IJKEDM.2017.10010630","url":null,"abstract":"The users of internet are growing exponentially providing a platform to the users where they can share ideas, their experiences or feedback regarding any product, services or any event. Nowadays, social media like Facebook, Twitter, blogs, micro-blog and others are very popular medium among the users for informal discussion or feedback. Some studies show that for effective decision making informal reviews, feedback or discussion should be considered. Sentiment may be positive or negative. As previous researches shows that there are two types of emotions positive or negative which can be measured by noting or counting of some words like 'not', 'no', 'bad', 'good', etc., in their conversation text. But the set of these words having crisp set characteristics or mere occurrences of these words do not explain the degree of sentiments. Therefore, this study develops an approach to measure the degree of sentiment of web data using fuzzy logic on the basis of membership value of linguistic hedges (e.i. very, mostly, small, highly etc.) in fuzzy set. This approach provides granularity of sentiments which is very useful for effective and reliable decision making process.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115560012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Knowledge discovery in time series data with contextual event identification 基于上下文事件识别的时间序列数据知识发现
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/ijkedm.2022.10049279
M. Velankar, V. Khatavkar, V. Jagtap, P. Kulkarni
{"title":"Knowledge discovery in time series data with contextual event identification","authors":"M. Velankar, V. Khatavkar, V. Jagtap, P. Kulkarni","doi":"10.1504/ijkedm.2022.10049279","DOIUrl":"https://doi.org/10.1504/ijkedm.2022.10049279","url":null,"abstract":"","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127920432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Building an annotated corpus for the Albanian language using bilingual projections and regular expressions 使用双语投影和正则表达式为阿尔巴尼亚语建立一个带注释的语料库
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2019.10020367
A. Kadriu
{"title":"Building an annotated corpus for the Albanian language using bilingual projections and regular expressions","authors":"A. Kadriu","doi":"10.1504/IJKEDM.2019.10020367","DOIUrl":"https://doi.org/10.1504/IJKEDM.2019.10020367","url":null,"abstract":"","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127111501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
New rules-based algorithm to improve Arabic stemming accuracy 一种新的基于规则的阿拉伯语词干提取算法
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2015.074082
Wael Chérif, Abdellah Madani, M. Kissi
{"title":"New rules-based algorithm to improve Arabic stemming accuracy","authors":"Wael Chérif, Abdellah Madani, M. Kissi","doi":"10.1504/IJKEDM.2015.074082","DOIUrl":"https://doi.org/10.1504/IJKEDM.2015.074082","url":null,"abstract":"In the recent past, the world has been witnessing a steady increase in the area of natural language processing owing to the spread of the internet. However, attempts and efforts devoted for Arabic language are still limited. By morphological and semantic properties, Arabic is considered a difficult language in the field of automatic processing. From that perspective, many different approaches were attempted to deal with the morphological variation and the agglutination phenomenon while stemming Arabic texts. Formally, stemming and light-stemming are used to remove irrelevant morphological variations from a given word, and extract its original stem or root. This research introduces a complete new rules-based algorithm. This involves precise removal of affixes based on context-sensitive morphological rules and then deduces the root according to a predefined set of rules. Finally, results show that the accuracy of the proposed algorithm is higher than the two well-known Arabic stemmers.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":" 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120832610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
An incremental approach for solution of text clustering problem 一种解决文本聚类问题的增量方法
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/ijkedm.2019.10023549
B. Ordin, D. Balli, Nur Uylas Sati
{"title":"An incremental approach for solution of text clustering problem","authors":"B. Ordin, D. Balli, Nur Uylas Sati","doi":"10.1504/ijkedm.2019.10023549","DOIUrl":"https://doi.org/10.1504/ijkedm.2019.10023549","url":null,"abstract":"","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128763174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An efficient algorithm for mining closed frequent intervals 一种高效的封闭频繁区间挖掘算法
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2018.10015619
N. Sarmah, A. Mahanta
{"title":"An efficient algorithm for mining closed frequent intervals","authors":"N. Sarmah, A. Mahanta","doi":"10.1504/IJKEDM.2018.10015619","DOIUrl":"https://doi.org/10.1504/IJKEDM.2018.10015619","url":null,"abstract":"","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128014802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
An associative rule-based classifier for Arabic medical text 基于关联规则的阿拉伯医学文本分类器
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2015.074071
Qasem A. Al-Radaideh, Samer Al-khateeb
{"title":"An associative rule-based classifier for Arabic medical text","authors":"Qasem A. Al-Radaideh, Samer Al-khateeb","doi":"10.1504/IJKEDM.2015.074071","DOIUrl":"https://doi.org/10.1504/IJKEDM.2015.074071","url":null,"abstract":"Text classification is one of the methods used for managing, organising and retrieving the needed data among the huge available text. Several methods have been proposed to manipulate the text classification problem. In recent years, some studies proposed the use of Associative Classification AC approach. This paper examines an associative classification approach for the categorisation of text typed in Arabic language and related to medical domain. The approach discovers a set of association rules to build a classification model where three steps were applied to build the model: generating association rules, rule ordering and pruning, and then validation. The results of the experiments showed that the ordered decision list approach outperforms other approaches with accuracy reaching 90.6%. In general, the results of the experiments showed that association rule mining is a suitable method for building good classification models to categorise Arabic medical text.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133891165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
A new constraint-based spatial clustering algorithm based on spatial adjacent relation for GML data 一种基于空间相邻关系的GML数据约束聚类算法
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2012.044705
V. Pattabiraman, R. Nedunchezhian
{"title":"A new constraint-based spatial clustering algorithm based on spatial adjacent relation for GML data","authors":"V. Pattabiraman, R. Nedunchezhian","doi":"10.1504/IJKEDM.2012.044705","DOIUrl":"https://doi.org/10.1504/IJKEDM.2012.044705","url":null,"abstract":"Spatial data mining (SDM) is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. Many methods on spatial clustering have been proposed, but only few of them considered the constraints like road, bridge, tunnel etc., that may present in the spatial data or remotely sensed imagery (RSI) data during the clustering process. The objective of this work is to identify the best constraint-based spatial clustering with help of the spatial adjacent relation and also discover the relationship between spatial and non-spatial attributes. Compared to other spatial clustering algorithms the constraint-based SCAR-GML (CSCAR-GML) clusters the spatial objects in the ideal way based on the spatial adjacent relations. The proposed CSCAR-GML computes the spatial adjacent relations among the spatial objects with the constraints and computing the spatial distance based on the similarity measure of the spatial objects. Then it clusters the spatial objects with the different spatial features according to the computed relations. The objects in one cluster are not nearer to each other, but they have similarity in spatial adjacent relation. The interesting simulation results have been achieved and reported. The experiments show that CSCAR-GML is better for spatial clustering with the constraints.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129492919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Event classification in foreign language aviation reports 外文航空报告中的事件分类
Int. J. Knowl. Eng. Data Min. Pub Date : 1900-01-01 DOI: 10.1504/IJKEDM.2016.10002664
Anil R. Yelundur, C. Giannella, Karine Megerdoomian, Craig Pfeifer
{"title":"Event classification in foreign language aviation reports","authors":"Anil R. Yelundur, C. Giannella, Karine Megerdoomian, Craig Pfeifer","doi":"10.1504/IJKEDM.2016.10002664","DOIUrl":"https://doi.org/10.1504/IJKEDM.2016.10002664","url":null,"abstract":"When adverse aviation events occur, narrative reports describing the events and their associated flights provide a valuable record for improving safety. Manual examination of large collections of such reports is challenging. Tools for automated event classification (assignment of type labels to individual reports) can help to mitigate this challenge. While several studies have developed and systematically empirically evaluated event classification tools on English aviation narratives, we are not aware of any that have done the same on foreign language narratives. We developed and implemented an approach for event classification based on Bayesian logistic regression and a novel feature selection technique. For comparison purposes, we also implemented an approach described in the literature. We collected and annotated a corpus of Japanese aviation incident reports, as well as, a corpus of French incident reports. We carried out a series of experiments comparing the accuracy of our approach and the other approach.","PeriodicalId":386151,"journal":{"name":"Int. J. Knowl. Eng. Data Min.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126709070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
首页 上一页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信