Department of BCA

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    Grammar And Context Based Approach For Identification And Translation Of Proverbs Using Trie-Based Ontology
    (International Journal of Computer Sciences and Engineering Vol.6, Special Issue.10, Nov 2018, 2018) Shaikh, Naziya
    Most current machine translation systems for translation from English to regional Indian languages ignore the presence of idioms in the text or return the exact literal meaning of the phrase in another language which loses the essence of the proverb. The main issues that arise include timely detection of the proverbs from a given paragraph and the separate processing required for translations of idioms into other languages. This paper presents a combination of natural language grammar-based approach and context-based approach towards detection of idioms in given English text and further presents a trie-based ontology that can be used to translate proverbs into regional languages. The grammar-based approach involves parsing English sentences and identifying the parts-of-speech tags and determining statistically the probability whether the given sentence is a proverb using certain grammar-based rules applicable for only proverbs. The context-based approach classifies and compares keywords in the proverbs and the keywords present in remaining part of the paragraph. Based on the combination of these two approaches, the proverb can be determined with better accuracy. For quick translation of detected proverbs into regional languages, keyword based priority search can be implemented on previously developed trie-based ontology using parts-of-speech tags.
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    Programming self-efficacy predictors in students of computer applications
    (Gyana, Vol XIV, No. 1 2018-19, 2018) Lemos, Mildred
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    A COMPARATIVE STUDY OF 10+2 LEVEL COURSES AND ITS IMPACT ON THE ACADEMIC PERFORMANCE OF THE STUDENTS STUDYING IN THIRD YEAR, BACHELOR IN COMPUTER APPLICATIONS
    (SHODH SARITA Vol. 7, Issue 26, April-June, 2020, 2020) Almeida, Tracy
    The evolving needs of technical education compel students at the 10+ 2 level to adhere to meet the needs of the entry level eligibility criteria. Therefore students who are unable to pursue Higher Education (HE) in engineering and other technical disciplines now stand a chance to enhance their technical knowledge through educational programmes like Bachelors in Computer Science, Bachelors in Computer Applications (BCA) and Bachelors in Information Technology. BCA is one such programme offered at the Goa University in the ten colleges across the state of Goa. College courses are fundamentally different from high school courses and there needs to be a proper choice of subject courses at 10+2 level that will help students to bridge the gap and to meet the standards of HE (Conley et al, 2007). This paper seeks to ascertain the influence of a few educational attributes at the 10+2 level on the performance at TY in the BCAprogramme. It also intends to provide suggestions to students who intend doing HE in the BCAprogramme. Keywords : Bachelor in Computer Applications (BCA), Mathematics (Math), Higher Education (HE), Computer Techniques (CT), 10+2 level, First Year (FY), Third Year(TY).
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    Effectiveness of different digital marketing strategies on Goan youth
    (INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY Volume 7 Issue 8 | ISSN: 2349-6002, 2020) Lemos, Mildred
    Digital Marketing encompasses the various strategies designed to help businesses optimize their presence thereby allowing them growth. It involves more than just displaying an advertisement, it uses Internet based advanced tools to research, manage, track and analyse web traffic. This paper studies the effectiveness and the impact of the different Digital Marketing strategies like Search Engine Optimization (SEO), Search Engine Marketing (SEM), Social Media Marketing (SMM), Influencer Marketing and E-mail Marketing on the youth in Goa
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    High Utility Itemset Mining Using Genetic Approach
    (Advanced Informatics for Computing Research pp 143–150, 2022) Almeida, Tracy; Khan, Salman
    Frequent Itemset Mining(FIM) aims to generate itemsets having their frequency of occurrence not lesser than minimum support specified by the user. FIM does not consider the itemset utility which is the it’s profit value. High-utility itemset mining(HUIM) mines high-utility itemsets(HUI) from data. HUIM is a combinatorial optimization. With HUIM algorithms, the time required to search increases exponentially with an increasing number of transactions and database items. To address this issue an efficient algorithm to mine HUIs is proposed. The proposed algorithm uses a compact form of chromosome encoding by eliminating the itemsets with low transactional utilities. The algorithm employs methodology of self mutation to reduce generation of unwanted chromosomes. Experimental results have shown that the proposed algorithm finds HUIs for a given threshold value. The proposed algorithm consumes less time as compared to another HUIM algorithm HUIM-IGA.
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    Efficient High Utility Itemset Mining Using Genetic Algorithms and Bit-Vector Optimization
    (Data Science and Security, 2024) Almeida, Tracy; Khan, Salman
    The paper focuses on High-Utility Itemset Mining (HUIM). The algorithms to mine high utility itemsets face exponential search time due to the growing number of transactions. An algorithm that employs genetic approach has been proposed in this paper to address this challenge. It utilizes techniques of genetic approach to avoid unfit individuals. Transaction clustering is also applied to the database, reducing the time required for database scanning during itemset utility calculations.
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    Time Series Cointegration Analysis of Major Indian Stocks
    (INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN TECHNOLOGY Volume 12 Issue 6, 2025) Lemos, Mildred
    Time Series Cointegration provides a powerful statistical framework for understanding the long-term interconnectedness of stock prices. This understanding is crucial for developing sophisticated trading strategies, managing risk effectively, and gaining deeper insights into the underlying dynamics of the stock market. This paper investigates the long-run equilibrium relationships among the major Indian stocks from diverse sectors listed on the Bombay Stock Exchange over a five-year period - April 2020 to March 2025. Employing the Engle-Granger two-step cointegration test on daily closing prices, we identify statistically significant cointegrated pairs, with HDFCBANK emerging as a central stock strongly linked with multiple banking and financial sector stocks. These findings indicate that deviations from equilibrium between these stocks tend to revert over time, reflecting stable long-term relationships. The results have important implications for portfolio management, pairs trading, risk mitigation, and strategic investment decisions within the Indian equity market.
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    Enhancing High-Utility Itemset Mining Efficiency Using Crow Search Algorithm with High-Utility Item Prioritization
    (Data Science and Security, 2025) Almeida, Tracy
    This study presents an enhanced Crow Search Algorithm (CSA) for High-Utility Itemset Mining (HUIM), aimed at improving efficiency in large-scale datasets. HUIM focuses on discovering itemsets based on utility, such as profit or importance, rather than mere frequency. Traditional algorithms struggle with large datasets due to the extensive search space, while metaheuristic approaches like CSA show promise but remain inefficient in handling low-utility itemsets. To address this, we introduce a high-utility item prioritization list to guide the CSA in selecting valuable itemsets, reducing computational complexity. Experimental results, using synthetic datasets, demonstrate that the enhanced CSA significantly reduces execution time as the minimum utility threshold increases. Despite the study’s limitations—such as the use of synthetic data and lack of comparisons with other algorithms—the proposed method showcases potential for practical applications like retail analysis.