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Purpose: Information extraction from big data is improved by either reducing the number of features in a data set or selecting features using intelligent data analysis. Generally, big data sets are complex to process using traditional approaches. Feature selection is highly essential in big data information extraction because it chooses the subset of features that influence the final classification. Reducing the number of selected features in the data leads to enhanced accuracy and efficiency of data extraction with other attributes used in the mathematical model. This work aims to improve the performance of the classifier using an enhanced binary bat algorithm-based effective feature selection model. formulated to enhance accuracy, efficiency of data extraction with other attributes. An enhanced binary bat algorithm (EBBA) proposed to solve the mentioned problem using local optimization and global optimization factor which improves the performance of optimization. Experiment carried out with different datasets selected to test effective performance of proposed algorithm and demonstrated performance is better with other algorithms. Design: The purpose of this paper is to provide, an effective feature selection model for big data information extraction. An enhanced binary bat algorithm has been proposed to improve attribute selection using local optimization and global optimization methods. Classification of multisource data using selected features using labeled approach. Particular Information extraction for multi view multi label (PIMM) approach is compared with EBBA algorithm. Further to enhance effectiveness of shared and specific information in big data [3] by setting the delta and omega factors in order to fuse different information from different view point, Online analysis of relevance with any redundancy analysis also been incorporated. Findings: All the experiments were carried out with different datasets on the number of iterations and fitness of the attributes to validate the effective performance of the proposed algorithm. Experimental results and graphs show that the proposed methodology improves the overall performance of optimization using PIMM models. Originality: A feature selection model based on the binary bat algorithm has been the focus of this paper. Subset selection and feature ranking are the two important methods used in this approach. Experiments were conducted on datasets to analyze the patterns in the number of iterations and fitness of the attributes over selection. The improvement in feature selection leads to better classification accuracy of the proposed model compared to other nature inspired techniques.

The Family is as a basic unit of society. According to August Comte family is a primary unit of the society. It a has link between individual and community. It is made up with parents and their children, who come from the same ancestor and living together in the same household. Family disorganization means breaking family relations, family crisis, bracken of marriage relationships, family dissolution, marital maladjustment, dissertation, separation, divorce etc,. It is called the conflict in marriage between family members. It is global problem. Marital conflict is inevitable and become part and parcel of life today but should handle carefully. Many disorganized people do not have the social stigma. The main reason for this is lack of adoption and understanding between couples. It effects on families parents, dependents and children. Some children from disorganized homes grow up to become social misfits and later graduate into delinquents and criminals. They may be maladjusted with people. According to Tim and Joy Downs in their book, The Seven Conflicts, couples who never learn how to effectively manage their conflicts begin a series of stages in their relationship that can ultimately destroy it.

Information extraction is systematic process of extracting structured information from documents which has both unstructured and semi structured data set. Data available over the web is unstructured which is processed and delivered that may be challenging due to massive data over web. Bigdata analytics approach is used in the computation field where massive data is managed and processed as information. Data from various sources like industries, institutes are processed using algorithms in efficient means employing web of things or Internet of things used to mine such a large data. Bio inspired algorithms have evolved from application of heuristic approaches to meta-heuristic and hyper-heuristic methodologies. Bio inspired techniques are categorized into human inspired algorithms, Swarm Intelligence algorithms, evolutionary algorithms and ecology based algorithms. Genetic algorithms are purely heuristic in nature and are employed for computation and extracting information and from big data. This improves the computation speed effectively for extracting web related information as evolutionary algorithm resolves information extraction problems. The Ant colony and Particle Swarm Intelligence algorithms are of meta-heuristic in nature. The Cuckoo search, Artificial Bee Colony, Firefly algorithm and Bat algorithms are of hyper heuristic in nature i.e., they employ a combination of methods. Web information extraction using bio inspired concepts and genetic operators increases efficiency, capability to search particular information in massive data in web. Some of the tools that are available for data extraction and mining are DataMelt, Apache Mahout, Weka, Orange and Rapid Miner for enhancing web data extraction efficiency. This survey on bio inspired methodologies can be extended to parameter tuning and controlling is another big strategy that can be implemented, in addition to convergence speed up.

Informes finales de los proyectos de investigacion 2017, financiados por el Fondo de Investigacion e Innovacion (FODEIN). Proyectos: Gobierno y Justicia Inteligente, -El dilema de los principios del derecho Legitimidad y Eficacia en las innovaciones publico digitales en Colombia-.Manual de Derecho Penal Internacional