{"title":"Semantic Approach for Classification of Web Services Using Unsupervised Normalized Similarity Measure","authors":"Shailja Sharma, J. Lather, M. Dave","doi":"10.4304/JETWI.6.3.364-372","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.364-372","url":null,"abstract":"Automatic or semiautomatic categorization of web services facilitates the relevant service retrieval as well as it helps the administrators in attaining globally consistent classification decisions that are independent of the administrator’s knowledge of application domain, organization of taxonomies and service characteristics. Lack of automatic mechanisms to help service publishers in the classification task, irrelevant and huge number of services returned by the UDDI, and lack of standard mechanisms that helps in the discovery of desired web services are some of the issues that need focus. In this paper, an automatic approach for service categorization is proposed that uses a lexical semantic network constructed from the web snippets as a knowledge base for semantic similarity calculation between the service profiles and the categories. Our approach involves mapping of service profiles to a category based dimension vector by using the notion of semantic similarity and aims at alleviating the administrator’s job by automatically providing them with a set of categories ranked based on the degree of semantic similarity. Empirical evaluation on a set of OWL-S services shows that the proposed approach helps in better decisions for relevant classification of services by giving an ordered set of categories based on the similarity scores.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683239","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}
Z. Al-Khanjari, Nasser Al-Hosni, N. Kraiem, Y. Jamoussi
{"title":"Developing E-Government Interoperability Driven Methodology","authors":"Z. Al-Khanjari, Nasser Al-Hosni, N. Kraiem, Y. Jamoussi","doi":"10.4304/JETWI.6.3.318-323","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.318-323","url":null,"abstract":"Developing e-Government interoperability in the government context is a complex task. As interoperability in government context is associated and hindered by many challenges and barriers connected to government nature of complexity. Interoperability is generally defined as the ability for two (or more) systems to exchange information and to use the information that has been exchanged. In this paper, we focus on computing systems interoperability across government ministries to achieve interoperable e-Government IT based solutions. In order to achieve e-Government interoperability in an organised and efficient way, this paper establishes a step-by-step e-Government Interoperability Driven Methodology. This contribution is motivated by the limitations of the traditional software engineering methodologies in terms of analysis, design and development frameworks to a point that they can hardly cope with the growing issues of e-Government services interoperability.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114768093","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}
{"title":"Green Scheduling of Bag-of-tasks Applications in Cloud Data Center Using GreenCloud Simulator","authors":"M. Premalatha, B. Ramakrishnan","doi":"10.4304/JETWI.6.3.273-279","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.273-279","url":null,"abstract":"The cloud provider provisions the resources of the data center to the user so as to satisfy the Quality of Service (QoS) negotiated between them and specified in the Service Level Agreements (SLA). To attain maximum profit, the cloud provider has to schedule the tasks in the data center efficiently in accordance to the users QoS requirements and also minimize the energy consumption thus reducing the operational expense (OPEX) of the data center. The energy efficient scheduling of cloud applications has to consider the QoS parameter specified as job deadline and assign them to minimum number of servers possible without affecting the performance so that the idle servers can be shutdown to reduce the energy consumed. This paper analyses this green scheduling for various workloads of the cloud users and provide information about the task completion and rejection at various data center load, the SLA violations and the degradation of system performance. It presents the server utilization specifying the number of busy and idle servers with their computational load and the energy consumed by them for different workloads. The paper also provides the insights on the utilization of the servers for the workloads and analyses the reasons for the underutilization of servers and how the scheduling can be improved without sacrificing the performance of the data center. The paper analyses the above observations of the green scheduling of the data center using GreenCloud.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116513095","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}
{"title":"Method of Semantic Web Service Discovery and Automatic Composition","authors":"Yuemin Wang, Jun Steed Huang","doi":"10.4304/JETWI.6.3.298-304","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.298-304","url":null,"abstract":"This paper investigates the semantic information-providing web service composition problem, and proposes a heuristic method of web service automatic composition based on a planning graph model. According to the characteristics of information-providing semantic web service discovery, the service composition is partitioned into two modules: the construction of the planning graph and the search for composition scheme. Thus the satisfaction of the service composition can be judged in polynomial bounded branching time. The rich relationship information from varying percentages of partial to full matched service network is fully considered in the construction process of the planning graph, and the search module of composition scheme further uses a corresponding heuristic service selection strategy. Finally, the experiments verify the efficiency and the strong adaptability of the automated method.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127688652","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}
{"title":"Improving the Quality of Machine Translation through Proper Transliteration of Name Entities","authors":"Deepti Bhalla, Nisheeth Joshi, Iti Mathur","doi":"10.4304/JETWI.6.3.354-358","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.354-358","url":null,"abstract":"Machine Translation is the study of system that translates the given input text in source language to the output text in the target language. The source language and the target language are Natural Languages. Machine Translation is a very difficult problem; especially name entity translation has always been a challenge for the machine translators because of different spelling variations in translation of name entities. In this paper we focus on improving the quality of our machine translated output. For this, at first we recognize the name entities and then transliterate them. We have calculated the phoneme based N-Gram Probabilities for all the name entities. Using these probabilities we are transliterating our name entities from English to Punjabi through syllabification in which we divide the word in to syllables.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130600399","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}
{"title":"Intelligent Rule Mining Algorithm for Classification over Imbalanced Data","authors":"V. Mangat, R. Vig","doi":"10.4304/JETWI.6.3.373-379","DOIUrl":"https://doi.org/10.4304/JETWI.6.3.373-379","url":null,"abstract":"Association rule mining for classification is a data mining technique for finding informative patterns from large datasets. Output is in the form of if-then rules containing attribute value combinations in antecedent and class label in the consequent. This method is popular for classification as rules are simple to understand and allow users to look into the factors leading to a specific class label. Rule mining methods based on swarm intelligence, specifically particle swarms, can effectively handle problems with large number of instances and mixed data. But the issue of classification over imbalanced datasets, wherein samples from one class greatly outnumber the other class, has not been fully investigated so far. A rule mining method based on Dynamic Particle Swarm and Ant Colony Optimizer that can handle data imbalance, has been proposed in this paper. Performance of the proposed algorithm has been compared with other state-of-the-art methods. Results indicate that in terms of quality, the proposed method outperforms other state-of-the-art methods.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121626004","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}
{"title":"An Improvised Algorithm for Relevant Content Extraction from Web Pages","authors":"Aanshi Bhardwaj, V. Mangat","doi":"10.4304/JETWI.6.2.226-230","DOIUrl":"https://doi.org/10.4304/JETWI.6.2.226-230","url":null,"abstract":"World Wide Web (WWW) is now a famous medium by which people all around the world can spread and gather information of all kind. However, there is large amount of irrelevant redundant and information on web pages also. Such information makes various web mining tasks web page crawling, web page classification, link based ranking and topic distillation complex. Previously, the relevant content was extracted only from textual part of web pages. But now-a-days the content on web page is not only in the text form but also as an image, video or audio. This paper proposes an improved algorithm for extracting informative content from web pages i.e. it extracts the relevant content not only as text but also as images, videos, audios, adobe flash files and online games. Experiments were conducted on different real websites show that precision and recall values of our approach is superior to the previous Word to Leaf Ratio approach.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125987172","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}
{"title":"Proposed Algorithm of Sentiment Analysis for Punjabi Text","authors":"Amandeep Kaur, Vishal Gupta","doi":"10.4304/JETWI.6.2.180-183","DOIUrl":"https://doi.org/10.4304/JETWI.6.2.180-183","url":null,"abstract":"Sentiment Analysis is to identify and classify the opinions/emotions/sentiments in written text. Till date, English Language includes most of the research work in this area. In this paper, we discussed the various approaches used to accomplish the sentiment analysis and research work done for Indian Languages like Hindi, Bengali and Telugu. We proposed an algorithm by using subjective lexicon which is created by using Hindi Subjective Lexicon. Our approach proves good performance on the testing data. We compared the results with already existing approaches.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"266 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117104842","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}
{"title":"A Survey of Existing Question Answering Techniques for Indian Languages","authors":"Poonam Gupta, Vishal Gupta","doi":"10.4304/JETWI.6.2.165-168","DOIUrl":"https://doi.org/10.4304/JETWI.6.2.165-168","url":null,"abstract":"With advancement in technology, the process of question answering is the main field of research of text mining. In this process user is assigned a particular answers in place of number of text documents or paragraphs. It provides a way for obtaining appropriate and useful answers for questions of user put in native natural language instead of formal query in that language. Hindi, Punjabi, Bengali, Kannada, Telugu and Marathi etc are main spoken languages in India. For these Indian languages, very less number of language resources is available and much of research is going on for developing basic language resources in these languages. This paper discusses a survey of different question answering techniques for Indian languages.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124669752","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}
{"title":"Enhancing Security Module to Prevent Data Hacking in Online Social Networks","authors":"M. Milton Joe, B. Ramakrishan","doi":"10.4304/JETWI.6.2.184-191","DOIUrl":"https://doi.org/10.4304/JETWI.6.2.184-191","url":null,"abstract":"Online Social Network (ONS) is the easiest platform to connect with one another. There are many Online Social Networking websites exist to bring up the reliable communication among the users. Facebook, Orkut, Google+, Twitter, MySpace, etc are some of the Online Social Networking websites. All the social networking websites provide the interface formally known as profile, to share their willingness with others. The users of these websites could share their feelings, photos, text file and even whatever the user wishes to provide. All the Online Social Networking websites bring the friends, family members and relatives together to share their desires in a fast track manner, however still it lacks in security module. The shared photos and information are freely open access to all the users of social networking websites. When the photos are freely available, the unauthorized users can easily access the photos of others and download it. Once the photo is downloaded, that image can be misused widely such as creation of fake profile and the photo can be sold to other nuisance websites. This kind of data hacking activities in online social networks even leads the life to death. In this paper, data hacking in online social network is considered and a novel mechanism is presented to prevent the data hacking.","PeriodicalId":311436,"journal":{"name":"Journal of Emerging Technologies in Web Intelligence","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779723","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}