International Confernce on Innovation Information in Computing Technologies最新文献_第3页

Ontology construction for explicit description of domain knowledge 构建本体，明确描述领域知识

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396079

R. Mervin, S. Murugesh, A. Jaya

引用次数: 0

Construction of Dependency Structure Matrix (DSM) for e-books using ontology based text mining 基于本体文本挖掘的电子书依赖结构矩阵(DSM)构建

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396097

K. Nanthini, R. Ramya

{"title":"Construction of Dependency Structure Matrix (DSM) for e-books using ontology based text mining","authors":"K. Nanthini, R. Ramya","doi":"10.1109/ICIICT.2015.7396097","DOIUrl":"https://doi.org/10.1109/ICIICT.2015.7396097","url":null,"abstract":"Dependency Structure Matrix (DSM) is a square matrix, used to map the dependencies between each entity/element. Such dependencies are examined to make out impacts. In general, college libraries maintain e-books for various departments, as students, research scholars in these days have started to refer e-books in most of the times. Since we don't have hard copies for some of the books, we go for searching e-books. This paper primarily focuses on finding related/linked/correlated/interrelated e-books that for a targeted e-book based on table of contents of each book. Related books will hold desired content that we require. Extract content page to ascertain the classes of e-books, ontology that provides inferences, regarding them. Subsequently, uses this ontology to discover the dependencies between each book and construct DSM which is used to represent related books as a result of comparing table of contents of each book. Subsequent to construction of DSM, it is converted into graph structure along with dependency level for easy analysis and find out. During arrival of fresh e-book to library, DSM is automatically updated by mining PDF and the graph is also updated along with their dependency level.","PeriodicalId":135283,"journal":{"name":"International Confernce on Innovation Information in Computing Technologies","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116901749","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

Catching target mobile node using time-of-arrival measurement in Wireless Sensor Networks 无线传感器网络中基于到达时间测量的目标移动节点捕获

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396105

J. Premalatha, P. Vijayakumari

{"title":"Catching target mobile node using time-of-arrival measurement in Wireless Sensor Networks","authors":"J. Premalatha, P. Vijayakumari","doi":"10.1109/ICIICT.2015.7396105","DOIUrl":"https://doi.org/10.1109/ICIICT.2015.7396105","url":null,"abstract":"Target localization and mobile node tracking problems in WSNs have been receiving considerable concentration recently, because of the requirements to achieve high localization accuracy, with the output of minimum cost. The drawback involved is the crisis of target tracking in Wireless Sensor Networks. Localization primarily refers to revealing of the spatial coordinates of a node. Target tracking deals with spatial coordinates discovery and movement tracking of a moving object. The mobile node location algorithms like weighted tracking methods and Arrival Time (AT) are insufficient for finding the location of the mobile device. The location estimation and weighted tracking method are mainly based on mobile target signal's Arrival Time (AT) measurement model. In this paper work, location tracking process can be achieved into two ways. At first part we find the location of the mobile node along with the extended weighted tracking method. This can be used to track the mobile device and to estimate the weight for the particular mobile node. Secondly, the concentration is towards the AT measurement model for measuring the signal arrival time. Finally, the proposed algorithm finds the location of the mobile device and improves the performance of the AT measurement model in different places.","PeriodicalId":135283,"journal":{"name":"International Confernce on Innovation Information in Computing Technologies","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128465386","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

Extraction of features for sentiment analysis using heterogenic domain 基于异质域的情感分析特征提取

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396093

P. Ajitha, D. V. Reddy

{"title":"Extraction of features for sentiment analysis using heterogenic domain","authors":"P. Ajitha, D. V. Reddy","doi":"10.1109/ICIICT.2015.7396093","DOIUrl":"https://doi.org/10.1109/ICIICT.2015.7396093","url":null,"abstract":"The overwhelming majority of existing approaches to opinion feature extraction accept mining patterns solely from one review language sets, identifying the different disparities in word spacing characteristics of opinion options across totally different language. In this work we have to consume the different opinion that is identifying through the sentiments, it is an important role in normal life-style. Users can express their thought, when user can sold or buy the commodities or products through the online are some different ways, then user can express their view through rating format. We have a tendency to capture this inequality via a live step known as domain relevancy (DR) that characterizes the relevancy of a term to a text assortment. We have a tendency to first extract an inventory of candidate opinion options from the domain review languages by shaping a collection of syntactic independent rules. User can express their views through three different ways that is \"A+\" means positive, \"A-\" means negative and \"A\" means neutral i.e., half chances, by finding this rating we are using User-Related Filtering (URF) Algorithm. For every extracted candidate feature, we have a tendency to estimate its user internal-domain relevance (UIDR)data and user external-domain relevance(UEDR) data scores on the domain-dependent and domain-independent review technique, severally. Candidate options that are minimum generic (UEDR score but a threshold) and additional domain-specific (UIDR score maximum than another threshold) are then confirmed as opinion options. Experimental results on real-world review domains show the planned UIEDR data approach to outmatch many alternative well-established ways to identifying opinion options.","PeriodicalId":135283,"journal":{"name":"International Confernce on Innovation Information in Computing Technologies","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123861372","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

High energy time domain temperature sensor for on chip thermal management 用于片上热管理的高能时域温度传感器

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396075

A. Elamaran, K. Amudha

引用次数: 0

KBRS — Keyword based recommendation system in social networks 社会化网络中基于关键词的推荐系统

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396081

Sandra Elizabeth Salim, R. Jebakumar

引用次数: 1

HS-TBAC a highly secured token based access control for outsourced data in cloud HS-TBAC是一种高度安全的基于令牌的访问控制，用于云中的外包数据

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396082

S. Senthilkumar, Madhu Viswanatham, M. Vinothini

引用次数: 2

Deduplication based storage and retrieval of data from cloud environment 基于重复数据删除的云环境数据存储和检索

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396092

N. Pritha, N. Velmurugan, S. Winster, A. Vijayaraj

引用次数: 3

A phoneme based model for english to malayalam transliteration 基于音素的英语马来拉姆语音译模型

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396078

C. Sunitha, A. Jaya

{"title":"A phoneme based model for english to malayalam transliteration","authors":"C. Sunitha, A. Jaya","doi":"10.1109/ICIICT.2015.7396078","DOIUrl":"https://doi.org/10.1109/ICIICT.2015.7396078","url":null,"abstract":"Transliteration plays an important role nowadays because it can be used for many applications such as text to speech conversion, Dubbing etc. The main purpose of Transliteration is to convert words from one language to another language such that their pronunciation will be same, but the meaning may be different. Transliteration is mainly classified into 4 models such as Phoneme based Transliteration Model, Correspondence based Transliteration Model, Grapheme based Transliteration Model, and Hybrid based Transliteration Model. Phoneme based transliteration takes the advantage of pronunciation and is better to implement when compared to other models. Research works are taking place in this field especially with Korean, Arabic, Chinese & Indian Languages. Very little work is being carried out with English to Malayalam Transliteration. At present Grapheme based transliteration is available for English - Malayalam transliteration. But there is a problem of pronunciation. This paper presents a Phoneme based transliteration model for English - Malayalam conversion which is based on pronunciation and works better than the Grapheme based model for the same. This model uses a pronunciation dictionary.","PeriodicalId":135283,"journal":{"name":"International Confernce on Innovation Information in Computing Technologies","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116073439","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: 8

A model for settting location privacy scheme in MANET 一种无线局域网中位置隐私方案的设置模型

International Confernce on Innovation Information in Computing Technologies Pub Date : 2015-02-01 DOI: 10.1109/ICIICT.2015.7396060

S. Raj, R. Srikkanthan, A. S. Kumar

引用次数: 0