Informatics Publishing Limited

Amita Jain ¹, Kamal Raj Pardasani ²

Affiliations
1 Department of Computer Application, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal 462 003, IN
2 Department of Mathematics, Bioinformatics and Computer Applications, Maulana Azad National Institute of Technology, Bhopal 462 003, IN

Abstract

Analysis of biological data plays an important role in medical and bioinformatics industry. However, uncertainty in this biological information is the most unavoidable challenge of this era. The existing algorithms for association rule mining are inadequate to address the issues of uncertainty in the molecular data. Variation in the length of the sequences leads to variation in the degree of relationships among amino acids. Ignorance of the parameters leads to uncertainty due to the dependencies of the objects and their patterns on the parameters. The degree of relationships among various amino acids present in the molecular sequences also depends on the parameters like length ranges and species, etc. In this article, a soft fuzzy set approach has been proposed for mining fuzzy amino acid associations in peptide sequences of Mycobacterium tuberculosis complex (MTBC). The approach is employed to incorporate the degree of relationships among amino acids present in the peptide sequences. The soft sets are employed to model relationships of amino acids with the parameters like length range, species etc. The amino acid associations and their relationships with various parameters in the peptide sequences of MTBC obtained in the present study will be of great use in developing signatures that will provide better insights into the structures, functions and interactions of proteins.

Keywords

Association Rule, Complex, Data Mining, Fuzzy and Soft Sets, Mycobacterium tuberculosis.

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Kanika Mittal ¹, Amita Jain ²

Affiliations
1 Department of Computer Science and Engineering, Bhagwan Parshuram Institute of Technology, IN
2 Department of Computer Science, Ambedkar Institute of Advanced Communication Technologies & Research, IN

Abstract

Query expansion (QE) is the process of reformulating a query to improve retrieval performance. Most of the times user's query contains ambiguous terms which adds relevant as well as irrelevant terms to the query after applying current query expansion methods. This results in to low precision. The existing query expansion techniques do not consider the context of the ambiguous words present in the user's query. This paper presents a method for resolving the correct sense of the ambiguous terms present in the query by determining the similarity of the ambiguous term with the other terms in the query and then assigning weights to the similarity. The weights to the similarity measures of the terms are assigned on the basis of decreasing order of distance to the ambiguous term. An aggregated similarity score based on the assigned weights is calculated using Ordered weighted averaging operator (OWA) for each sense of the ambiguous term and the sense having highest similarity score will be considered as the most appropriate sense for the ambiguous term. After then, the query is expanded by taking an implicit feedback from user and adding terms related to the corresponding sense and hence optimizing the query expansion process.

Keywords

Query Expansion, Natural Language Processing, Information Retrieval, Word Sense Disambiguation, WordNet, OWA Operator.

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Amita Jain ¹, Rajeev Kansal ²

Affiliations
1 University College, Punjabi University, Patiala, Dhilwan (Barnala), Punjab, IN
2 Punjabi University, Patiala, Punjab, IN

Abstract

In the Business environment of the fast changing technological growth and communication system there are requirements for human resources having Intelligence Quotient (IQ), Emotional Quotient (EQ) and Spiritual Quotient (SQ). The SQ and EQ are useful in handing intrapersonal and interpersonal relationship whereas IQ helps to take logical decisions. This paper presents the results of an investigation aimed to explore the relation between Spiritual Intelligence and Emotional Intelligence among commerce students. The research is based on the purposive sample selected from students of M.Com, Commerce Department of Punjabi University, Patiala. For data collection and scoring of variables, methodology used by Zainuddin Ahmed namely ROQAN Spiritual Intelligence test (RSIT) and ROQAN Emotional Intelligence test (REIT) are followed. The statistical analysis of Pearson’s product moment method of correlation is calculated. Finding of the paper is that significant positive relationship exists between Spiritual Intelligence and Emotional Intelligence (along with its dimensions) among commerce students.

Keywords

Commerce Students, Emotional Intelligence, Intelligence Quotient, Relationship, Spiritual Intelligence.

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