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Ponnusamy, R.
- Web Enabled Real Time Weather Data Analysis
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Authors
Affiliations
1 Sathyabama University, Chennai, IN
2 Madha Engineering College, Kundrathur, Chennai, IN
1 Sathyabama University, Chennai, IN
2 Madha Engineering College, Kundrathur, Chennai, IN
Source
Indian Journal of Science and Technology, Vol 6, No 11 (2013), Pagination: 5507–5513Abstract
In this paper, a web enabled software tool is developed for Meteorological Information System, with Query, Visualization and Data Reporting features for the Meteorological Network. A state of the art Data Acquisition System has (DAS) been designed and implemented at 50m Meteorological Tower in Chennai. This tool is used to generate the multilevel micrometeorological data with tower based measurements and provide the same for wind field modeling studies. The salient feature of the 50m meteorological tower has been established to receive real time meteorological data for predicting research based models in both academic and industries.Keywords
Meteorological Data, Weather-info, Real-time WeatherFull Text
References
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- Data Preprocessing and Cleansing in Web Log on Ontology for Enhanced Decision Making
Abstract Views :200 |
PDF Views:0
Authors
Affiliations
1 Department of Computer Science and Engineering, Sathyabama University, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, IN
2 Rajiv Gandhi College of Engineering, Chennai – 602105, Tamil Nadu, IN
1 Department of Computer Science and Engineering, Sathyabama University, Jeppiaar Nagar, Chennai – 600119, Tamil Nadu, IN
2 Rajiv Gandhi College of Engineering, Chennai – 602105, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 10 (2016), Pagination:Abstract
Background/Objectives: Web applications are growing at a massive promptness and its users rise at exponential speed. The deviations in technology have made it potential to capture the user’s essence and interactions with web applications through web log file. Methods/Statistical Analysis: Due to huge amount of extraneous data in the web log, the original log file cannot be openly used in the Web Usage Mining (WUM) system. The web server log files used for mining several expedient patterns to analyze the access behavior of the user. Data pre-processing plays a dynamic role in Data Mining. Findings: We propose a new web log mining method for determining web access procedure from interpreted web usage logs which integrates data on user behaviors through self-rating and communication tracking. The raw data is preprocessed in order to improve the quality of data to be extracted. We discuss the significance of information pre-processing method and abundant steps elaborate in receiving the essential information effectively. This pre-processing method used to process and analysis the web log data for extraction of user search patterns. The fuzzy association rule minimizes users’ exploration period and facilitate for enhance decision making. Applications/Improvements: The proposed data cleaning method removes the extraneous records from web log. With this progression, we create a Personalized Ontology, which assists various semantic web applications such as site perfection, business intelligence and recommendations for behavioral analysis. Finally, we illustrate the efficiency of this method by the experimental results in the framework of data pre-processing and cleansing extraneous data for personalized ontology.Keywords
Behavioral Tracking, Data Preprocessing, Knowledge Discovery, Ontology Creation, Weblog MiningFull Text
- Text Classification:A Concept Matrix based Approach
Abstract Views :127 |
PDF Views:0
Authors
R. Ponnusamy
1,
T. V. Gopal
2
Affiliations
1 Dept. of Computer Science and Engineering, Anna University, Chennai 600 025, IN
2 A.A.M. Eneineerine Colleee. Kovilvenni 614 403, IN
1 Dept. of Computer Science and Engineering, Anna University, Chennai 600 025, IN
2 A.A.M. Eneineerine Colleee. Kovilvenni 614 403, IN
Source
Information Studies, Vol 12, No 3 (2006), Pagination: 179-195Abstract
Text classification is an important tasic in modem information systems. Most of the existing classification techniques are keyword and statistical oriented. Keyword alone cannot always distinguish between the relevant and irrelevant text. The meaning of a key word is context dependent. When it occurs in a phrase it can be quite different from its meaning as in individual word. In many cases the keyword-based approach does not bring out the semantic meaning of a document. In this paper a new hierarchical conceptmatrix patterned automated classification method has been designed and developed. Also this is not solely based on key words. The design involves development of an agent by adapting the ACM Computing Review classification method. The formulation of a new concept matrix consisting of phrases occurring in the title, abstract and keywords of an experimental research document is proposed. The columns of the matrix are representing the different phrases and rows are frequency of occurrences of a specified phrase in the document. For a set of documents in a corpus such row matrices are created. In order to classify a new document its new concept matrix is created and appended to the existing matrix. After this a SVD is performed over the concept matrix, decomposing the original matrix into three matrices. Then the original matrix is reconstructed using certain rows with highest convergence value of diagonal and orthonormal matrices. After the original reconstruction, the correlation between the columns represents the relativity of the document. The system is able to learn and formulate the new concept-matrix at the various level hierarchies over a period of time. This concept matrix hierarchy pattern also gives the semantic meaning. An agent is able to decide the relevance of the document with respect to its own hierarchy as well as able to add the phrases and required conceptmatrix in to the servers that are predicted under a certain category. The system is tested with a set of articles collected through Internet.
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