C: Software & Data Engineering (217)
GJCST: C
A Frame Work for Text Mining using Learned Information Extraction System
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 Text mining is a very exciting research area as it tries to discover knowledge from unstructured texts. These texts can be found on a computer desktop, intranets and the internet. The aim of this paper is to give an overview of text mining in the contexts of its techniques, application domains and the most challenging issue. The Learned Information Extraction (LIE) is about locating spec...
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Authors M.Vasavi, Sathish KuppaniRead Journal Click Here
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Page No. 41 to 50
Evolution of Object-Oriented Database Systems
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 Data basesare quintessential part of most modern web and mobile applications. In most part, relational databases dominate the database market but the evolution of object-oriented databases has provided users and developers with an alternative option. Object-oriented databases provide a number of advantages over relational databases like ease of extensibility, custom data models, provisio...
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Authors Hibatullah AlzahraniRead Journal Click Here
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Page No. 37 to 40
Isotropic Dynamic Hierarchical Clustering
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 We face a business need of discovering a pattern in locations of a great number of points in a high-dimensional space. We assume that there should be a certain structure, so that in some locations the points are close while in other locations the points are more dispersed. Our goal is to group the close points together. The process of grouping close objects is known under the name of clu...
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Authors Victor Sadikov, Oliver Rutishauser,Read Journal Click Here
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Page No. 29 to 36
Bottom-up Update Mechanism for Re-structured Complete Binary Trees
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 This paper introduces a bottom-up update mechanism together with a non-recursive initial update procedure that reduces the required extra memory space and computational overhead. A new type of tree is defined based on a different geometrical interpretation of Complete Binary Trees. The new approach paves the way for a special and practical initialization of the tree, which is a prerequis...
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Authors Mevlut BulutRead Journal Click Here
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Page No. 11 to 19
Crop Coverage Data Classification using Support Vector Machine
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 A statistical tool which can be used in various applications ranging from medical science to agricultural science is support vector machines. The proposed methodology used is support vector machine and it isused to classify a raster map. The dataset used herein is of Gujarat state agriculture map. The proposed approach is used to classify raster map into groups based on crop coverage of ...
Guiding Software Developers using Automated Adaptation of Object Ensembles Plug-in
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 2 Software developing process has been improving day by day. The development process can be affected through different ways like changing the development environment, strategies and upcoming technologies. In order to save valuable times and to speed up the process, we can guide programmer during the development time through providing relevant recommendations. There are some strategies that...
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Authors Ziaur Rahman, Md. Abir Hosain, Md. Badrul Alam Miah, Md. Hadifur RahmanRead Journal Click Here
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Page No. 27 to 34
A Systematic Review of Learning based Notion Change Acceptance Strategies for Incremental Mining
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 2 The data generated contemporarily from different communication environments is dynamic in content different from the earlier static data environments. The high speed streams have huge digital data transmitted with rapid context changes unlike static environments where the data is mostly stationery. The process of extracting, classifying, and exploring relevant information from enormous f...
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Authors D.S.S.K.Dhanalakshmi, Dr. Ch.SuneethaRead Journal Click Here
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Page No. 17 to 26
A Fitness Function for Search-based Testing of Java Classes, which is Based on the States Reached by the Object under Test
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 2 Genetic Algorithms are among the most efficient search-based techniques to automatically generate unit test cases today. The search is guided by a fitness function which evaluates how close an individual is to satisfy a given coverage goal. There exists several coverage criteria but the default criterion today is branch coverage. Nevertheless achieving high or full branch coverage does n...
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Authors Ina Papadhopulli , Elinda Meu00c3u00a7eRead Journal Click Here
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Page No. 5 to 15
Research on Big Data Analytics
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 2 This paper gives an insight in the scope of Big Data in the field of Geoscience and which scripting language is acceptable for Big Data.Big Data transforms traditional information to customary conviction of how data should be aggregated, processed, analysed and stored. Big data is rudimentary transfiguring world of science. The large volume of data is posing a great menace on scientists....
5M: Multi-Instance Multi-Cluster based Weakly Supervised MIL Model for Multimedia Data Mining
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 3 The high pace rise in online as well as offline multimedia unannotated data and associated mining applications have demanded certain efficient mining algorithm. Multiple instance learning (MIL) has emerged as one of the most effective solutions for huge unannotated data mining. Still, it requires enhancement in instance selection to enable optimal mining and classification of huge multim...
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Authors Girisha GS, Dr. K. Udaya KumarRead Journal Click Here
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Page No. 21 to 28
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A Neuro Fuzzy Algorithm to Compute Software Effort Estimation
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 1 Software Effort Estimation is highly important and considered to be a primary activity in software project management. The accurate estimates are conducted in the development of business case in the earlier stages of project management. This accurate prediction helps the investors and customers to identify the total investment and schedule of the project. The project developers define pr...
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Authors N. Shivakumar, N. Balaji, K. AnanthakumarRead Journal Click Here
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Page No. 23 to 28
Cluster Analysis of Medical Research Data using R
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 1 Cluster analysis divides the data into groups that are meaningful, useful or both. It is also used as a starting point for other purposes of data summarization. This paper discuss some very basic algorithms like K-means, Fuzzy C-means, Hierarchical clustering to come up with clusters, and use R data mining tool. The results are tested on the datasets namely Online News Popularity, Iris D...
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Authors Lavanya Pamulaparty, Dr. C. V Guru Rao, Dr. M. Sreenivasa RaoRead Journal Click Here
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Page No. 17 to 22
On Database Relationships versus Mathematical Relations
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 1 Unfortunately, the widespread used one-to-many, many-to-one, one-to-one, and many-tomany database relationships lack precision and are very often leading to confusions that affect the quality of conceptual data modeling and database design. This paper advocates replacing them with the rigorous math notions of relations and (one-to-one) functions. ...
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Authors Christian MancasRead Journal Click Here
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Page No. 13 to 16
Social Recommendation Algorithm Research based on Trust Influence
Published In: GJCST Part: C: Software & Data Engineering Volume: 16 Issue: 1 Cold start and data sparsity greatly affect the recommendation quality of collaborative filtering. To solve these problems, social recommendation algorithms introduce the corresponding user trust information in social network, however, these algorithms typically utilize only adjacent trusted user information while ignoring the social network connectivity and the differences in the trust ...
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Authors Xue Yi, Hong Yinghan, Chen PinghuaRead Journal Click Here
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Page No. 5 to 12