Concept relation extraction using Naïve Bayes classifier for ontology-based question answering systems

Domain ontology is used as a reliable source of knowledge in information retrieval systems such as question answering systems. Automatic ontology construction is possible by extracting concept relations from unstructured large-scale text. In this paper, we propose a methodology to extract concept relations from unstructured text using a syntactic and semantic probability-based Naïve Bayes classifier. We propose an algorithm to iteratively extract a list of attributes and associations for the given seed concept from which the rough schema is conceptualized. A set of hand-coded dependency parsing pattern rules and a binary decision tree-based rule engine were developed for this purpose. This ontology construction process is initiated through a question answering process. For each new query submitted, the required concept is dynamically constructed, and ontology is updated. The proposed relation extraction method was evaluated using benchmark data sets. The performance of the constructed ontology was evaluated using gold standard evaluation and compared with similar well-performing methods. The experimental results reveal that the proposed approach can be used to effectively construct a generic domain ontology with higher accuracy. Furthermore, the ontology construction method was integrated into the question answering framework, which was evaluated using the entailment method

Comparative Study of Hyperelliptic Curve Cryptosystem over Prime Field and Its Survey

Public key cryptography is the famous cryptography technique used in many corporate sectors for developing software to provide security services. Hyperelliptic Curve Cryptosystem (HECC) is one of the public key cryptographic technique, an expansion of Elliptic Curve Cryptography which offers the similar level of security compared with other cryptosystems such as RSA, ECC and DSA. HECC supervise the ECC due to shorter operand size. This paper will analysis the performance of HECC over genus curve 2, 3, 4, 5, 6 and compares the result with ECC. It also inspects the use of Hyperelliptic Curve Cryptography technique and affords complete survey on its performance for many applications

DNA based Password Authentication Scheme using Hyperelliptic Curve Cryptography for Smart Card

Abstract — Smart Card technology is the emerging technology which is developing among common masses in our culture and widely used in the sectors of banking and industries. Many research works are undergoing in this area to provide highly confidential data transmission. Existing Scheme provides a security against offline attack for the lost Smart Card using Elliptic Curve Cryptography (ECC) but it requires more communication and computation overhead with higher key length. To overcome this limitation, DNA based Password authentication using Hyper Elliptic Curve Cryptography (HECC) scheme is proposed. It provides more security than existing system which allows server and smartcard to exchange the generated password and verify each other. This system exploits the advantages of Hyperelliptic Curve Cryptography (HECC) technique which is having lesser key size, less communication and computation overhead for Password generation and signature verification process