Word similarity assessment is one of the most important elements in Natural Language Processing (... more Word similarity assessment is one of the most important elements in Natural Language Processing (NLP) and information retrieval. Evaluating semantic similarity of concepts is a problem that has been extensively investigated in the literature in different areas, such as artificial intelligence, cognitive science, databases and software engineering. Semantic similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Currently, its importance is growing in different settings, such as digital libraries, heterogeneous databases and in particular the Semantic Web. In this paper, authors present a search engine framework using Google API that expands the user query based on similarity scores of each term of user’s query. The authors calculated the semantic similarity of noun words to obtain the related concepts described by the search query using WordNet. Users query is replaced with concepts discovered from the similarity measures. Authors present a new approach to compute the semantic similarity between words. A common data set of word pairs is used to evaluate the proposed approach: first calculate the semantic similarities of 30 word pairs, then the correlation coefficient between human judgement and three computational measures are calculated, the experimental result shows new approach is better than other existing computational models.
The security of computer networks has been in the focus of research for years. Organizations have... more The security of computer networks has been in the focus of research for years. Organizations have realized that network security technology has become very important in protecting its information. Any attempt, successful or unsuccessful to compromise the confidentiality, integrity and availability of any information resource or the information itself is considered as a security threat or an intrusion. Every day, new kinds of threats are being faced by industries. One of the way-out to this problem is by using Intrusion Detection System (IDS). The main function of IDS is distinguishing and predicting normal or abnormal behaviors. This paper presents new implementation strategy performing the intrusion detection system, which gives better results by improving accuracy of classification. This approach is based on by defining addition and deletion rule and updating policy for intrusion detection. The experimental results, conducted on the KDD99 dataset, prove that, this new approach outperforms several state-of-the-art methods, particularly in detecting rare attack types.
2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2020
Digital Forensics has become noted field in the last few years. One of the areas in digital foren... more Digital Forensics has become noted field in the last few years. One of the areas in digital forensics is Digital Camera Identification. This paper proposed a camera identification framework, which is based on the Gray Level Cooccurrence Matrix (GLCM) features. The Photo Response Non-Uniformity (PRNU) noise is a kind of sensor finger impression, which permits to extraordinarily distinguish the camera that took an image. It is estimated from the denoised images using a denoised filter. Then estimate the Gray level Co-occurrence Matrix (GLCM) features of the PRNU noise pattern. A Scaled Conjugate Gradient (SCG) Backpropagation Neural Network is used for classification.
2021 International Conference on Emerging Smart Computing and Informatics (ESCI), 2021
The sparse old age historical Modi documents are archived in government and non-government sector... more The sparse old age historical Modi documents are archived in government and non-government sectors from long time. These documents are pasted on card-sheet like material for preservation. In the processes of intelligent archaic Modi document recognition system there is a need to detect the actual page area before to other preprocessing stages. Over the past period there has been a growing interest in addressing of object detection of document images or removal of clutter noise. However, no comprehensive studies have been exists which are work on the proposed problem statement. This paper presents page boundary extraction and page area detection approach for highly degraded chronic handwritten Modi document images. This algorithm is based on the analysis of the gray level frequency of the document image with statistical scrutiny. The ground-truth region-based evaluation methods are used to evaluate and compare the results. Actual page area of the ancient handwritten Modi document images is detected 97% proficiently without affecting its originality. The proposed approach is robust and efficient compared with state-of-art techniques.
3 A divide-and-conquer based algorithm is presented here to detect the skew angle in handwritten ... more 3 A divide-and-conquer based algorithm is presented here to detect the skew angle in handwritten old age Modi document images. The skew angle detection range is estimated by determining the inclination of the document image. A new horizontal projection profile based criterion function is proposed and used here to compute the concentration of the black pixels. The criterion function is scrutinized to estimate the rotational angle range and detect the skew angle of the document image. The results prove that the proposed technique has corrected skew angle in diverse types of document images. This method accurately identifies skew angle in the clockwise or anticlockwise direction in estimated rotational angle range up to ±89 degree with angular resolution 0.1 degree. The Modi Lipi document image dataset and benchmark online datasets are used to test and compare the performance of the proposed approach.
One of the major research areas in data science is deep learning. Convolutional Neural Networks p... more One of the major research areas in data science is deep learning. Convolutional Neural Networks play a huge role in the recent success of the artificial intelligence-based applications. Cursive character recognition is still an active research problem from many years. This paper deals with recognition of offline handwritten Marathi documents written in MODI script using deep learning convolutional neural network model. The algorithm explained in this paper makes use of Rectified Linear Unit neuron activation function in the convolutional layers as it gives better performance and computationally least expensive and softmax neuron activation function in its fully connected layer. The max pooling layer is used for feature detection. The model designed uses 32 convolutional filters of size 3 × 3 × 1. The model developed is trained by using more than 40000-character samples belonging to 31 different class labels. The trained neural network is tested on more than 10000-character samples f...
... Content-Based Image Retrieval Using Region-Based Shape Descriptor 131 Jagadeesh Pujari,Pushpa... more ... Content-Based Image Retrieval Using Region-Based Shape Descriptor 131 Jagadeesh Pujari,Pushpalatha SN and Padmashree Desai 18. ... and Denoising Using Modified Non-Linear 940 Diffusion (MAD) Approach Akhilesh R. Upadhyay, Ramesh K. Choudhary and Sanjay N ...
Static signature verification has a significant use in establishing the authenticity of bank chec... more Static signature verification has a significant use in establishing the authenticity of bank checks, insurance and legal documents based on the signatures they carry. As an individual signs only a few times on the forms for opening an account with any bank or for insurance related purposes, the number of genuine signature templates available in banking and insurance applications is limited, a new approach of static handwritten signature verification based on Dynamic Time Warping (DTW) by using only five genuine signatures for training is proposed in this paper. Initially the genuine and test signatures belonging to an individual are normalized after calculating the aspect ratios of the genuine signatures. The horizontal and vertical projection features of a signature are extracted using discrete Radon transform and the two vectors are combined to form a combined projection feature vector. The feature vectors of two signatures are matched using DTW algorithm. The closed area formed b...
Communications in Computer and Information Science
With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data ... more With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data are increasing day by day. Mining these data towards the corporate and government has become a broad area of research under Natural Language Processing. Sentiment Analysis (SA), identification of the public's attitude, using machine learning or subjective lexicon, is easier for resource-rich languages like English. Still, for Marathi being poor resource language, it's a difficult task. In this research, the three approaches have experimented-Corpus-based, SentiWordNet3.0-based, and Hindi Senti-WordNet (HSWN)-based to create the Marathi sentiment lexicon (adjective, adverb). The first two approaches use Google Translator to make use of English resource-SWN3.0. The third approach uses HSWN and Marathi WordNet, which minimizes translation errors. The word coverage of the SWN3.0-based lexicon is noteworthy. This paper attempts the Marathi subjective lexicon creation for the first time, which would aid for SA chore precise to the Marathi data.
Generally each user has a different background and different needs when he/she searches for any i... more Generally each user has a different background and different needs when he/she searches for any information on the web. For the same query issued by different users, most of the search engines return the same results to all users, without considering the individuals need. This problem is solved using personalized web search. In this paper, we propose the architecture for web search personalization using web usage mining without user’s explicit feedback. The proposed architecture uses an efficient sequential access pattern mining algorithm based on CSB-mine algorithm, a new approach for sessionization and modified user profile. The proposed mining algorithm does not generate any costlier tree and it avoids construction of projected database at any stage. Our experimental results on synthetic data set show that proposed algorithm performs better than the CSB-mine algorithm in terms of run time and average memory usage. Then experiments are carried out on proxy server logs for personal...
Evaluating semantic similarity of concepts is a problem that has been extensively investigated in... more Evaluating semantic similarity of concepts is a problem that has been extensively investigated in the literature in different areas, such as artificial intelligence, cognitive science, databases and software engineering. Semantic similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Currently, it is growing in importance in different settings, such as digital libraries, heterogeneous databases and in particular the Semantic Web. In such contexts, very often concepts are organized according to taxonomy (or a hierarchy). We investigate approaches to compute the semantic similarity between natural language terms. This paper presents new approach for measuring semantic similarity between words and hierarchical structure is used to present information content. In this paper, we present a search engine using Google API that expands the user query based on similarity scores of each term of user’s query. Users query words ar...
2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016
Recommender systems are needed due to information overload in the field of libraries. These syste... more Recommender systems are needed due to information overload in the field of libraries. These systems are different than search engines by the way that profiles of users are learned and accordingly recommendations are provided to the users. Agent based framework for developing such recommender system is proposed. The experiment shown cosine similarity is better measure to find similarity distance between vectors of user profiles and library resources than Euclidean, Manhattan, and Chebyshev measures. The recommendation results are further improved by assigning weights to the semantic concepts. This paper also describes about weight assignment to improve the recommendations.
Word similarity assessment is one of the most important elements in Natural Language Processing (... more Word similarity assessment is one of the most important elements in Natural Language Processing (NLP) and information retrieval. Evaluating semantic similarity of concepts is a problem that has been extensively investigated in the literature in different areas, such as artificial intelligence, cognitive science, databases and software engineering. Semantic similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Currently, its importance is growing in different settings, such as digital libraries, heterogeneous databases and in particular the Semantic Web. In this paper, authors present a search engine framework using Google API that expands the user query based on similarity scores of each term of user’s query. The authors calculated the semantic similarity of noun words to obtain the related concepts described by the search query using WordNet. Users query is replaced with concepts discovered from the similarity measures. Authors present a new approach to compute the semantic similarity between words. A common data set of word pairs is used to evaluate the proposed approach: first calculate the semantic similarities of 30 word pairs, then the correlation coefficient between human judgement and three computational measures are calculated, the experimental result shows new approach is better than other existing computational models.
The security of computer networks has been in the focus of research for years. Organizations have... more The security of computer networks has been in the focus of research for years. Organizations have realized that network security technology has become very important in protecting its information. Any attempt, successful or unsuccessful to compromise the confidentiality, integrity and availability of any information resource or the information itself is considered as a security threat or an intrusion. Every day, new kinds of threats are being faced by industries. One of the way-out to this problem is by using Intrusion Detection System (IDS). The main function of IDS is distinguishing and predicting normal or abnormal behaviors. This paper presents new implementation strategy performing the intrusion detection system, which gives better results by improving accuracy of classification. This approach is based on by defining addition and deletion rule and updating policy for intrusion detection. The experimental results, conducted on the KDD99 dataset, prove that, this new approach outperforms several state-of-the-art methods, particularly in detecting rare attack types.
2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2020
Digital Forensics has become noted field in the last few years. One of the areas in digital foren... more Digital Forensics has become noted field in the last few years. One of the areas in digital forensics is Digital Camera Identification. This paper proposed a camera identification framework, which is based on the Gray Level Cooccurrence Matrix (GLCM) features. The Photo Response Non-Uniformity (PRNU) noise is a kind of sensor finger impression, which permits to extraordinarily distinguish the camera that took an image. It is estimated from the denoised images using a denoised filter. Then estimate the Gray level Co-occurrence Matrix (GLCM) features of the PRNU noise pattern. A Scaled Conjugate Gradient (SCG) Backpropagation Neural Network is used for classification.
2021 International Conference on Emerging Smart Computing and Informatics (ESCI), 2021
The sparse old age historical Modi documents are archived in government and non-government sector... more The sparse old age historical Modi documents are archived in government and non-government sectors from long time. These documents are pasted on card-sheet like material for preservation. In the processes of intelligent archaic Modi document recognition system there is a need to detect the actual page area before to other preprocessing stages. Over the past period there has been a growing interest in addressing of object detection of document images or removal of clutter noise. However, no comprehensive studies have been exists which are work on the proposed problem statement. This paper presents page boundary extraction and page area detection approach for highly degraded chronic handwritten Modi document images. This algorithm is based on the analysis of the gray level frequency of the document image with statistical scrutiny. The ground-truth region-based evaluation methods are used to evaluate and compare the results. Actual page area of the ancient handwritten Modi document images is detected 97% proficiently without affecting its originality. The proposed approach is robust and efficient compared with state-of-art techniques.
3 A divide-and-conquer based algorithm is presented here to detect the skew angle in handwritten ... more 3 A divide-and-conquer based algorithm is presented here to detect the skew angle in handwritten old age Modi document images. The skew angle detection range is estimated by determining the inclination of the document image. A new horizontal projection profile based criterion function is proposed and used here to compute the concentration of the black pixels. The criterion function is scrutinized to estimate the rotational angle range and detect the skew angle of the document image. The results prove that the proposed technique has corrected skew angle in diverse types of document images. This method accurately identifies skew angle in the clockwise or anticlockwise direction in estimated rotational angle range up to ±89 degree with angular resolution 0.1 degree. The Modi Lipi document image dataset and benchmark online datasets are used to test and compare the performance of the proposed approach.
One of the major research areas in data science is deep learning. Convolutional Neural Networks p... more One of the major research areas in data science is deep learning. Convolutional Neural Networks play a huge role in the recent success of the artificial intelligence-based applications. Cursive character recognition is still an active research problem from many years. This paper deals with recognition of offline handwritten Marathi documents written in MODI script using deep learning convolutional neural network model. The algorithm explained in this paper makes use of Rectified Linear Unit neuron activation function in the convolutional layers as it gives better performance and computationally least expensive and softmax neuron activation function in its fully connected layer. The max pooling layer is used for feature detection. The model designed uses 32 convolutional filters of size 3 × 3 × 1. The model developed is trained by using more than 40000-character samples belonging to 31 different class labels. The trained neural network is tested on more than 10000-character samples f...
... Content-Based Image Retrieval Using Region-Based Shape Descriptor 131 Jagadeesh Pujari,Pushpa... more ... Content-Based Image Retrieval Using Region-Based Shape Descriptor 131 Jagadeesh Pujari,Pushpalatha SN and Padmashree Desai 18. ... and Denoising Using Modified Non-Linear 940 Diffusion (MAD) Approach Akhilesh R. Upadhyay, Ramesh K. Choudhary and Sanjay N ...
Static signature verification has a significant use in establishing the authenticity of bank chec... more Static signature verification has a significant use in establishing the authenticity of bank checks, insurance and legal documents based on the signatures they carry. As an individual signs only a few times on the forms for opening an account with any bank or for insurance related purposes, the number of genuine signature templates available in banking and insurance applications is limited, a new approach of static handwritten signature verification based on Dynamic Time Warping (DTW) by using only five genuine signatures for training is proposed in this paper. Initially the genuine and test signatures belonging to an individual are normalized after calculating the aspect ratios of the genuine signatures. The horizontal and vertical projection features of a signature are extracted using discrete Radon transform and the two vectors are combined to form a combined projection feature vector. The feature vectors of two signatures are matched using DTW algorithm. The closed area formed b...
Communications in Computer and Information Science
With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data ... more With the hike of social networking sites like Facebook, Twitter, Instagram, the Marathi web data are increasing day by day. Mining these data towards the corporate and government has become a broad area of research under Natural Language Processing. Sentiment Analysis (SA), identification of the public's attitude, using machine learning or subjective lexicon, is easier for resource-rich languages like English. Still, for Marathi being poor resource language, it's a difficult task. In this research, the three approaches have experimented-Corpus-based, SentiWordNet3.0-based, and Hindi Senti-WordNet (HSWN)-based to create the Marathi sentiment lexicon (adjective, adverb). The first two approaches use Google Translator to make use of English resource-SWN3.0. The third approach uses HSWN and Marathi WordNet, which minimizes translation errors. The word coverage of the SWN3.0-based lexicon is noteworthy. This paper attempts the Marathi subjective lexicon creation for the first time, which would aid for SA chore precise to the Marathi data.
Generally each user has a different background and different needs when he/she searches for any i... more Generally each user has a different background and different needs when he/she searches for any information on the web. For the same query issued by different users, most of the search engines return the same results to all users, without considering the individuals need. This problem is solved using personalized web search. In this paper, we propose the architecture for web search personalization using web usage mining without user’s explicit feedback. The proposed architecture uses an efficient sequential access pattern mining algorithm based on CSB-mine algorithm, a new approach for sessionization and modified user profile. The proposed mining algorithm does not generate any costlier tree and it avoids construction of projected database at any stage. Our experimental results on synthetic data set show that proposed algorithm performs better than the CSB-mine algorithm in terms of run time and average memory usage. Then experiments are carried out on proxy server logs for personal...
Evaluating semantic similarity of concepts is a problem that has been extensively investigated in... more Evaluating semantic similarity of concepts is a problem that has been extensively investigated in the literature in different areas, such as artificial intelligence, cognitive science, databases and software engineering. Semantic similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Currently, it is growing in importance in different settings, such as digital libraries, heterogeneous databases and in particular the Semantic Web. In such contexts, very often concepts are organized according to taxonomy (or a hierarchy). We investigate approaches to compute the semantic similarity between natural language terms. This paper presents new approach for measuring semantic similarity between words and hierarchical structure is used to present information content. In this paper, we present a search engine using Google API that expands the user query based on similarity scores of each term of user’s query. Users query words ar...
2016 International Conference on Global Trends in Signal Processing, Information Computing and Communication (ICGTSPICC), 2016
Recommender systems are needed due to information overload in the field of libraries. These syste... more Recommender systems are needed due to information overload in the field of libraries. These systems are different than search engines by the way that profiles of users are learned and accordingly recommendations are provided to the users. Agent based framework for developing such recommender system is proposed. The experiment shown cosine similarity is better measure to find similarity distance between vectors of user profiles and library resources than Euclidean, Manhattan, and Chebyshev measures. The recommendation results are further improved by assigning weights to the semantic concepts. This paper also describes about weight assignment to improve the recommendations.
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Papers by Satish Kolhe