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9. Experiments with Different Indexing Techniques for Text Retrieval tasks on Gujarati Language using Bag of Words Approach

Author

Pareek, Jyoti, Joshi, Hardik, Chauhan, Krunal, and Patel, Rushikesh

Subjects
Computer Science - Information Retrieval, Computer Science - Digital Libraries
Abstract

This paper presents results of various experiments carried out to improve text retrieval of gujarati text documents. Text retrieval involves searching and ranking of text documents for a given set of query terms. We have tested various retrieval models that uses bag-of-words approach. Bag-of-words approach is a traditional approach that is being used till date where the text document is represented as collection of words. Measures like frequency count, inverse document frequency etc. are used to signify and rank relevant documents for user queries. Different ranking models have been used to quantify ranking performance using the metric of mean average precision. Gujarati is a morphologically rich language, we have compared techniques like stop word removal, stemming and frequent case generation against baseline to measure the improvements in information retrieval tasks. Most of the techniques are language dependent and requires development of language specific tools. We used plain unprocessed word index as the baseline, we have seen significant improvements in comparison of MAP values after applying different indexing techniques when compared to the baseline.

Published
2020

10. A Study on the Stock Market Trend Predictions

Author

Thomas, Rosemol, Joshi, Hiren, Joshi, Hardik, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Choudrie, Jyoti, editor, Mahalle, Parikshit N., editor, Perumal, Thinagaran, editor, and Joshi, Amit, editor

Published
2023
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11. Colorizing Black and White Images Using Deep ConvNets and GANs

Author

Ahlawat, Savita, Choudhary, Amit, Wadhwa, Chirag, Joshi, Hardik, Shokeen, Rohit, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Khanna, Ashish, editor, Polkowski, Zdzislaw, editor, and Castillo, Oscar, editor

Published
2023
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13. Performance Comparison of Different Diversity and Combining Techniques Over Gamma–Gamma FSO Link

Author

Joshi, Hardik, Gupta, Shilpi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Dhavse, Rasika, editor, Kumar, Vinay, editor, and Monteleone, Salvatore, editor

Published
2023
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15. Experiments on Manual Thesaurus based Query Expansion for Ad-hoc Monolingual Gujarati Information Retrieval Tasks

Author

Joshi, Hardik and Pareek, Jyoti

Subjects
Computer Science - Information Retrieval
Abstract

In this paper, we present the experimental work done on Query Expansion (QE) for retrieval tasks of Gujarati text documents. In information retrieval, it is very difficult to estimate the exact user need, query expansion adds terms to the original query, which provides more information about the user need. There are various approaches to query expansion. In our work, manual thesaurus based query expansion was performed to evaluate the performance of widely used information retrieval models for Gujarati text documents. Results show that query expansion improves the recall of text documents., Comment: arXiv admin note: substantial text overlap with arXiv:1209.0126

Published
2020

26. A Mathematical Model to Study the Role of Buffer and ER Flux on Calcium Distribution in Nerve Cells

Author

Joshi, Hardik, Jha, Brajesh Kumar, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Sahni, Manoj, editor, Merigó, José M., editor, Jha, Brajesh Kumar, editor, and Verma, Rajkumar, editor

Published
2021
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28. Improving Diabetes Prediction by Selecting Optimal K and Distance Measures in KNN Classifier.

Author

Hameed, Emad Majeed and Joshi, Hardik

Subjects
TREATMENT of diabetes, K-nearest neighbor classification, MACHINE learning, EUCLIDEAN distance, PREDICTION models
Abstract

Diabetes is an illness that is widespread throughout the world and is considered a health concern, which requires work to explore advanced predictive techniques for early diagnosis of the illness. This paper discusses diabetes prediction by using the K-Nearest Neighbors (KNN) classifier, which is a widely used algorithm in machine learning. Most studies only dealt with investigating the optimal value of k in the KNN algorithm and did not address the best method to measure distance alone or together with the optimal value of k to improve the efficiency of diabetes prediction. This study simultaneously investigates both the optimal value of k and the optimal method for measuring distance to improve the performance of the KNN technique in predicting diabetes. By using and analyzing the Indian Diabetes PIMA dataset, this study seeks to discover the extent to which different parameters, especially the optimal value of K and distance metrics, affect the performance of the classifier. Through experiments that included applying different values for the K factor and using various distance measures, the study reached insights into maximizing the classifier's accuracy. The study shows that choosing the distance measure greatly affects the accuracy of classification and selecting the optimal K value helps eliminate problems of overfitting and underfitting, which is a feature of robust models for diabetes prediction. The research results showed that the best performance achieved was 80.5% when k=35 and the Euclidean distance measure was used. [ABSTRACT FROM AUTHOR]

Published
2024
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31. From Citation count to Argumentation count: a new metric to indicate the usefulness of an article

Author

Joshi, Hardik

Subjects
Computer Science - Information Retrieval, Computer Science - Digital Libraries
Abstract

Citation count is a quantifiable measure to indicate the number of times an article is cited by other articles. It is believed that if an article is cited often then it must be an important or influential article; however, there is no guarantee that the most cited articles are good in quality. In this paper, the author suggests argumentation count, a new metric for citation analysis. The proposed metric, argumentation count is a triplet of quantities for each concept of an article that helps in providing a quantifiable measure about the usefulness of an article., Comment: Technical Conference cum Workshop on Digital Library Using DSpace hosted by Gujarat National Law University on 21-23 March, 2013

Published
2014

33. Evaluation of some Information Retrieval models for Gujarati Ad hoc Monolingual Tasks

Author

Joshi, Hardik J. and Jyoti, Pareek

Subjects
Computer Science - Information Retrieval
Abstract

This paper describes the work towards Gujarati Ad hoc Monolingual Retrieval task for widely used Information Retrieval (IR) models. We present an indexing baseline for the Gujarati Language represented by Mean Average Precision (MAP) values. Our objective is to obtain a relative picture of a better IR model for Gujarati Language. Results show that Classical IR models like Term Frequency Inverse Document Frequency (TF_IDF) performs better when compared to few recent probabilistic IR models. The experiments helped to identify the outperforming IR models for Gujarati Language., Comment: 6 pages, Some text in Gujarati Language

Published
2012

37. Performance comparison of machine learning techniques in prediction of diabetes risk.

Author

Hameed, Emad Majeed and Joshi, Hardik

Subjects
*MACHINE learning, *MACHINE performance, *PEOPLE with diabetes, *DIABETES, *CARBOHYDRATE metabolism, *BLOOD sugar
Abstract

One of the major factors for rising death rates around the world is diabetes. Diabetes is a condition that occurs due to a deficiency, inefficiency, or inadequate secretion of the hormone insulin in the patient body, and from chronic problems that affect carbohydrate metabolism and rise blood glucose levels. The rising rates of diabetes require scientific works to early predict diabetes for the prevention and treatment. Researchers have recognized the effectiveness of classification models created using machine learning approaches for disease prediction. In relation to diabetes, researchers are working to provide data-based scientific methods for detecting the disease. The aim of this study is to classify people based on their diabetes condition using different machine learning methods. Two datasets are utilized for this purpose; Pima dataset collected from Indian society and dataset obtained from Iraqi society. The results show that Logistic Regression has highest accuracy of 0.77% when applying Pima dataset, while Gradient Boosting Classifier gives best performance with accuracy 0.977 when using Iraqi society dataset. [ABSTRACT FROM AUTHOR]

Published
2024
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47. Modeling the spatiotemporal intracellular calcium dynamics in nerve cell with strong memory effects.

Author

Joshi, Hardik and Jha, Brajesh Kumar

Subjects
*NEURONS, *INTRACELLULAR calcium, *FINITE difference method, *FINITE element method, *CELL death
Abstract

Calcium signaling in nerve cells is a crucial activity for the human brain to execute a diversity of its functions. An alteration in the signaling process leads to cell death. To date, several attempts registered to study the calcium distribution in nerve cells like neurons, astrocytes, etc. in the form of the integer-order model. In this paper, a fractional-order mathematical model to study the spatiotemporal profile of calcium in nerve cells is assembled and analyzed. The proposed model is solved by the finite element method for space derivative and finite difference method for time derivative. The classical case of the calcium dynamics model is recovered by setting the fractional parameter and that validates the model for classical sense. The numerical computations have systematically presented the impact of a fractional parameter on nerve cells. It is observed that calbindin-D28k provides a significant effect on the spatiotemporal variation of calcium profile due to the amalgamation of the memory of nerve cells. The presence of excess amounts of calbindin-D28k controls the intracellular calcium level and prevents the nerve cell from toxicity. [ABSTRACT FROM AUTHOR]

Published
2023
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