使用權重動態視窗之密度導向的局部離群值偵測演算法

廖又葳

3.236.16.13，Hello！

Close
Search Quick Search Advanced Search Publication Search	Personal Service Member Login Searching History Use Bonus Card SYMSKAN
Browse Browse by University of Graduate Thesis Browse by Pinyin of Graduate Thesis Browse by Conference Proceedings Topic Browse by Conference Proceedings Publisher Browse by Pinyin of Conference Proceedings Browse by eBook Category Browse by eBook Topic Browse by eBook Publisher
Customer Services Authorize Airiti Recommend a Journal

Search Symbol (Half-width)	Description of Search Symbols
Space	"AND" indicates the intertwining of key terms used in a search
Double Quotation Marks ("") ( " " )	Double quotation marks indicate the beginning and end of a phrase, and the search will only include terms that appear in the same order of those within the quotations. Example: "image process" ： " image process "
?	Indicates a variable letter. Entering two ? will indicate two variable letters, and so on. Example: "Appl?", search results will yield apple, apply… e , appl y … ( (often used to English word searches) )
*	Indicates an unlimited number of variable letters to follow, from 1~n. Example: Enter "appl*", search results will yield apple, apples, apply, applied, application…(often used in English word searches) e , appl es , appl y , appl ied , appl ication … ( (often used to English word searches) )
AND、OR、NOT	Boolean logic combinations of key words is a skill used to expand or refine search parameters. (1) AND (1) AND: Refines search parameters (2) OR (2) OR: Expands search parameters (3) NOT: Excludes irrelevant parameters

DOI stands for Digital Object Identifier （ D igital O bject I dentifier ） ,
and is the unique identifier for objects on the internet. It can be used to create persistent link and to cite articles.

Using DOI as a persistent link

To create a persistent link, add「http://dx.doi.org/」「 http://dx.doi.org/ 」 before a DOI.
For instance, if the DOI of an article is 10.5297/ser.1201.002 , you can link persistently to the article by entering the following link in your browser: http://dx.doi.org/ 10.5297/ser.1201.002 。
The DOI link will always direct you to the most updated article page no matter how the publisher changes the document's position, avoiding errors when engaging in important research.

Cite a document with DOI

When citing references, you should also cite the DOI if the article has one. If your citation guideline does not include DOIs, you may cite the DOI link.

DOIs allow accurate citations, improve academic contents connections, and allow users to gain better experience across different platforms. Currently, there are more than 70 million DOIs registered for academic contents. If you want to understand more about DOI, please visit airiti DOI Registration （ doi.airiti.com ）。

Data Source

Basic & Applied Sciences > Information Science
College of Electrical Engineering & Computer Science > Department of Computer Science and Engineering

Bibliography Management Tool

Related Links

Report an Issue

Purchase Single Articles

Download PDF

使用權重動態視窗之密度導向的局部離群值偵測演算法

A New Density-Based Local Outlier Detection Algorithm Using Weighted Dynamic Window

廖又葳 , Masters　　Advisor：吳俊霖　　

英文

局部離群值偵測；非監督式離群值偵測；異常值偵測；密度導向之離群值偵測；動態視窗；權重賦予；權重動態視窗； Local outlier ； Unsupervised Outlier Detection ； Anomaly Detection ； Density-Based Outlier Factor ； Dynamic window ； Weighting assignment ； Weighted dynamic window

Abstract │ Reference (16) │ Altmetrics

Abstract 〈TOP〉

Parallel Abstract 〈TOP〉

An outlier is an observation sample that is distant from other observations. The outlier detection method area one of the important research topics in data analysis and pattern recognition, it has been widely used in various knowledge domains. The focus of this study is on the local outlier detection, i.e., a sample is dissimilar to its surrounding data (not global dataset). The existing density-based outlier detection algorithm - local outlier factor (LOF) has the following problems: (1) It can’t perform well when the dataset is imbalanced or their density distributions are overlapped; (2) It is sensitive to the selection of the parameter k in finding nearest neighbors. This study aims at implement a better performance density-based outlier detection method which can solve above problems. By using the dynamic window and the weighting assignment, the proposed method can detect the outlier effectively and robustly. Experiments on synthetic and real world datasets demonstrate that our proposed method yields robust and excellent performance.

Reference ( 16 ) 〈TOP〉

[2]. V. Chandola, A. Banerjee and V. Kumar, "Anomaly detection", ACM Computing Surveys, vol. 41, no. 3, pp. 1-58, 2009.
連結：
[5]. S. Ramaswamy, R. Rastogi and K. Shim, "Efficient algorithms for mining outliers from large data sets", ACM SIGMOD Record, vol. 29, no. 2, pp. 427-438, 2000.
連結：
[8]. H. Fan, O. Zaïane, A. Foss and J. Wu, "Resolution-based outlier factor: detecting the top-n most outlying data points in engineering data", Knowledge and Information Systems, vol. 19, no. 1, pp. 31-51, 2008.
連結：
[14]. E. Schubert, A. Zimek and H. Kriegel, "Local outlier detection reconsidered: a generalized view on locality with applications to spatial, video, and network outlier detection", Data Mining and Knowledge Discovery, vol. 28, no. 1, pp. 190-237, 2012.
連結：
[1]. V. Barnett and T. Lewis, Outliers in statistical data, 3rd ed. Chichester [u.a.]: Wiley, 1994.

Altmetrics

〈TOP〉

E-mail ：

When an article is available to download, a notice will be sent to your mailbox address.

E-mail ：