Vishal Jain

Work place: Bharati Vidyapeeth's Institute of Computer Applications and Management (BVICAM), New Delhi, INDIA

E-mail: vishaljain83@ymail.com

Website:

Research Interests: Computer Science & Information Technology, Computer Architecture and Organization, Information Systems, Information Retrieval, World Wide Web, Information Theory

Biography

Vishal Jain has completed his M.Tech (CSE) from USIT, Guru Gobind Sidgh Indraprastha University, Delhi and doing Ph.D from Engineering Department, Lingaya’s Computer Science and University, Faridabad. Presently he is working as Assistant Professor in Bharati Vidyapeeth’s Institute of Computer Applications and Management, (BVICAM), New Delhi. His research area includes Web Technology, Semantic Web and Information Retrieval. He is also associated with CSI, ISTE.

Author Articles
Artificial Intrusion Detection Techniques: A Survey

By Ashutosh Gupta Bhoopesh Singh Bhati Vishal Jain

DOI: https://doi.org/10.5815/ijcnis.2014.09.07, Pub. Date: 8 Aug. 2014

Networking has become the most integral part of our cyber society. Everyone wants to connect themselves with each other. With the advancement of network technology, we find this most vulnerable to breach and take information and once information reaches to the wrong hands it can do terrible things. During recent years, number of attacks on networks have been increased which drew the attention of many researchers on this field. There have been many researches on intrusion detection lately. Many methods have been devised which are really very useful but they can only detect the attacks which already took place. These methods will always fail whenever there is a foreign attack which is not famous or which is new to the networking world. In order to detect new intrusions in the network, researchers have devised artificial intelligence technique for Intrusion detection prevention system. In this paper we are going to cover what types evolutionary techniques have been devised and their significance and modification.

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Ontology Based Information Retrieval in Semantic Web: A Survey

By Vishal Jain Mayank Singh

DOI: https://doi.org/10.5815/ijitcs.2013.10.06, Pub. Date: 8 Sep. 2013

In present age of computers, there are various resources for gathering information related to given query like Radio Stations, Television, Internet and many more. Among them, Internet is considered as major factor for obtaining any information about a given domain. When a user wants to find some information, he/she enters a query and results are produced via hyperlinks linked to various documents available on web. But the information that is retrieved to us may or may not be relevant. This irrelevance is caused due to huge collection of documents available on web. Traditional search engines are based on keyword based searching that is unable to transform raw data into knowledgeable representation data. It is a cumbersome task to extract relevant information from large collection of web documents. These shortcomings have led to the concept of Semantic Web (SW) and Ontology into existence. Semantic Web (SW) is a well defined portal that helps in extracting relevant information using many Information Retrieval (IR) techniques. Current Information Retrieval (IR) techniques are not so advanced that they can be able to exploit semantic knowledge within documents and give precise result. The terms, Information Retrieval (IR), Semantic Web (SW) and Ontology are used differently but they are interconnected with each other. Information Retrieval (IR) technology and Web based Indexing contributes to existence of Semantic Web. Use of Ontology also contributes in building new generation of web- Semantic Web. With the help of ontologies, we can make content of web as it will be markup with the help of Semantic Web documents (SWD’s). Ontology is considered as backbone of Software system. It improves understanding between concepts used in Semantic Web (SW). So, there is need to build an ontology that uses well defined methodology and process of developing ontology is called Ontology Development.

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Ontology Development and Query Retrieval using Protégé Tool

By Vishal Jain Mayank Singh

DOI: https://doi.org/10.5815/ijisa.2013.09.08, Pub. Date: 8 Aug. 2013

This paper highlights the explicit description about concept of ontology which is concerned with the development and methodology involved in building ontology. The concept of ontologies has contributed to the development of Semantic Web where Semantic Web is an extension of the current World Wide Web in which information is given in a well-defined meaning that translates the given unstructured data into knowledgeable representation data thus enabling computers and people to work in cooperation. Thus, we can say that Semantic Web is information in machine understandable form. It is also called as Global Information Mesh (GIM). Semantic Web technology can be used to deal with challenges including traditional search engines and retrieval techniques within given organizations or for e-commerce applications whose initial focus is on professional users. Ontology represents information in a manner so that this information can also be used by machines not only for displaying, but also for automating, integrating, and reusing the same information across various applications which may include Artificial Intelligence, Information Retrieval (IR) and many more. Ontology is defined as a collection of set of concepts, their definitions and the relationships among them represented in a hierarchical manner that is termed as Taxonomy. There are various tools available for developing ontologies like Hozo, DOML, and AltovaSemantic Works etc. We have used protégé which is one of the most widely used ontology development editor that defines ontology concepts (classes), properties, taxonomies, various restrictions and class instances. It also supports several ontology representation languages, including OWL. There are various versions of protégé available like WebProtege 2.0 beta, Protégé 3.4.8, Protégé 4.1 etc. In this paper, we have illustrated ontology development using protégé 3.1 by giving an example of Computer Science Department of University System. It may be useful for future researchers in making ontology on protégé version 3.1.

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