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2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)最新文献

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Co-Clustering with Side Information for Text mining 基于侧信息的文本挖掘协同聚类
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684152
Ramya Elizabeth Thomas, S. Khan
{"title":"Co-Clustering with Side Information for Text mining","authors":"Ramya Elizabeth Thomas, S. Khan","doi":"10.1109/SAPIENCE.2016.7684152","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684152","url":null,"abstract":"Many of the text mining applications contain a huge amount of information from document in the form of text. This text can be very helpful for Text Clustering. This text also includes various kind of other information known as Side Information or Metadata. Examples of this side information include links to other web pages, title of the document, author name or date of Publication which are present in the text document. Such metadata may possess a lot of information for the clustering purposes. But this Side information may be sometimes noisy. Using such Side Information for producing clusters without filtering it, can result to bad quality of Clusters. So we use an efficient Feature Selection method to perform the mining process to select that Side Information which is useful for Clustering so as to maximize the advantages from using it. The proposed technique, CCSI (Co-Clustering with Side Information) system makes use of the process of Co-Clustering or Two-mode clustering which is a data mining technique that allows concurrently clustering of the rows and columns of a matrix.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131736958","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: 4
Exploring the Similarity/Dissimilarity measures for unsupervised IDS 探索无监督IDS的相似/不相似度量
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684160
P. S. R. Murty, R. K. Kumar, M. Sailaja
{"title":"Exploring the Similarity/Dissimilarity measures for unsupervised IDS","authors":"P. S. R. Murty, R. K. Kumar, M. Sailaja","doi":"10.1109/SAPIENCE.2016.7684160","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684160","url":null,"abstract":"This paper investigates various Similarity/Dissimilarity measures for Intrusion Detection Problem. In this paper we implemented an offline Anomaly based IDS using agglomerative and partition based clustering algorithms with selected Similarity/Dissimilarity measures. In unsupervised learning labeling the clusters is an important task. This paper employed two cluster labeling algorithms, SNC labeling algorithm and “labeling clusters using class representative objects”. This work is evaluated using KDDCup 99 dataset.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132903201","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
Game balancing with ecosystem mechanism 基于生态系统机制的游戏平衡
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684145
Wen Xia, Bhojan Anand
{"title":"Game balancing with ecosystem mechanism","authors":"Wen Xia, Bhojan Anand","doi":"10.1109/SAPIENCE.2016.7684145","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684145","url":null,"abstract":"To adapt game difficulty upon game character's strength, Dynamic Difficulty Adjustment (DDA) and some other learning strategies have been applied in commercial game designs. However, most of the existing approaches could not ensure diversity in results, and rarely attempted to coordinate content generation and behaviour control together. This paper suggests a solution that is based on multi-level swarm model and ecosystem mechanism, in order to provide a more flexible way of game balance control.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134265026","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: 7
Generic code Cloning method for detection of Clone code in software Development 软件开发中克隆代码检测的通用代码克隆方法
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684149
Syed Haque, V. Srikanth, E. Reddy
{"title":"Generic code Cloning method for detection of Clone code in software Development","authors":"Syed Haque, V. Srikanth, E. Reddy","doi":"10.1109/SAPIENCE.2016.7684149","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684149","url":null,"abstract":"The major part of risk the development of software or programs is existence of duplicate code that can affect the software maintainability. The main aim of Clone identification technique is to search and detect the parts of the software code which is identical. In the passed there are various techniques that are used to identify and reflect the code identity and code fragments. Code cloning reduces the time and effort of the software developer but it also decreases the quality of the software like readability, changeability and increases maintainability. So, code clone has to be detected to reduce the cost of maintenance to some extent. In this paper, a new Generic technique is purposed to detect code clone from various input source codes (from web, disk and etc.,) by segmenting the code into number of sub-programs or modules or functions. I propose a technique that can detect 1-type, 2-type, 3-type and 4-type clones efficiently.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134456747","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: 6
Quality improvement in Color Extended Visual Cryptography using ABM and PRWP 利用ABM和PRWP提高彩色扩展视觉密码的质量
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684159
Alkha Mohan, V. Binu
{"title":"Quality improvement in Color Extended Visual Cryptography using ABM and PRWP","authors":"Alkha Mohan, V. Binu","doi":"10.1109/SAPIENCE.2016.7684159","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684159","url":null,"abstract":"Visual Cryptography is a secret sharing techniquue to hide secret data on images. It uses human visual system for decryption. In Color Extended Visual Cryptography (Color EVS) secret data is shared in meaningful color images. Error diffusion technique is used for digital halftoning. Use of Additional Basis Matrix (ABM) and Perfect Reconstruction of White Pixel (PRWP) technique improve the quality of decrypted image.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124455601","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
Classifying library resources in Library Recommender Agent using PU learning approach 基于PU学习方法的图书馆推荐代理中图书馆资源分类
2016 International Conference on Data Mining and Advanced Computing (SAPIENCE) Pub Date : 2016-03-01 DOI: 10.1109/SAPIENCE.2016.7684162
S. B. Shirude, S. Kolhe
{"title":"Classifying library resources in Library Recommender Agent using PU learning approach","authors":"S. B. Shirude, S. Kolhe","doi":"10.1109/SAPIENCE.2016.7684162","DOIUrl":"https://doi.org/10.1109/SAPIENCE.2016.7684162","url":null,"abstract":"Agent based Library Recommender System is proposed with the objective to provide effective and intelligent use of library resources such as finding right book/s, relevant research journal papers and articles. The architecture consists of profile agent and library recommender agent. The main task of Library recommender agent is filtering and providing recommendations. Library resources include book records having table of contents, journal articles including abstract, keywords. Rich set of keywords are obtained to compute similarity via table of contents and abstracts. The library resources are classified into fourteen categories specified in ACM computing classification system 2012 (ACM CCS). The identified category provides a way to obtain semantically related keywords for the library resources. This paper provides the task of library resources classification using PU (Positive Unlabeled) learning approach implemented using NB (Naïve Bayes) Classifier. Recommendation accuracy of the system is improved by library resources classification. The novel features of the recommender system are use of ACM CCS 2012 as ontology, semantic similarity computation, implicit auto update of user profiles, and variety of users in evaluation.","PeriodicalId":340137,"journal":{"name":"2016 International Conference on Data Mining and Advanced Computing (SAPIENCE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123345924","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: 4
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