Papers by JAGADISH KALLIMANI
Smart innovation, systems and technologies, 2024
Smart innovation, systems and technologies, Dec 31, 2022
Smart Innovation, Systems and Technologies, 2022
2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)
Lecture notes in networks and systems, Nov 6, 2022
Lecture notes in electrical engineering, 2022
Lecture notes in electrical engineering, 2022
International Journal of Advanced Computer Science and Applications
Author attribution is the field of deducing the author of an unknown textual source based on cert... more Author attribution is the field of deducing the author of an unknown textual source based on certain characteristics inherently present in the author's style of writing. Author attribution has a ton of useful applications which help automate manual tasks. The proposed model is designed to predict the authorship of the Kannada text using a sequential neural network with Bi-Directional Long Short Term Memory layers, Dense layers, Activation function and Dropout layers. Based on the nature of the data, we have used stochastic gradient descent as an optimizer that improves the learning of the proposed model. The model extracts Part of the speech tags as one of the semantic features using the N-gram technique. A Conditional random fields model is developed to assign Part of the speech tags for the Kannada text tokens, which is the base for the proposed model. The parts of the speech model achieve an overall 90% and 91% F1 score and accuracy respectively. There is no state-of-art model to compare the performance of our model with other models developed for the Kannada language. The proposed model is evaluated using the One Versus Five (1 vs 5) method and overall accuracy of 77.8% is achieved.
2017 International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT)
In this digital age, natural language is causing hindrance in the advancement of information tech... more In this digital age, natural language is causing hindrance in the advancement of information technology revolution in India. There is a need to perform Natural Language Processing (NLP) using computer processing, so that computer based systems can be accessible through natural languages like Hindi. Therefore a language translator is very important tool to resolve this problem. One of the key challenges involved in the design of a language translator is Polysemy disambiguation. Polysemy means having two or more meanings to a single word. For language translation operations, it is crucial to find the right meaning of any given word in its context. This is known as Word Sense Disambiguation (WSD). Various resources and tools already exist for WSD in English language while regional languages have not been equally explored yet. This project has a user interface where the user enters a meaningful sentence in Hindi with polysemy word. The system identifies the polysemous word/s if any in the sentence and lists one or more meanings associated with the polysemous word. Using existing machine learning techniques the project identifies the right meaning of the polysemous word based on the given context.
Wireless Communications and Mobile Computing
Wireless networks include a set of nodes which are connected to one another via wireless links fo... more Wireless networks include a set of nodes which are connected to one another via wireless links for communication purposes. Wireless sensor networks (WSN) are a type of wireless network, which utilizes sensor nodes to collect and communicate data. Node localization is a challenging problem in WSN which intends to determine the geographical coordinates of the sensors in WSN. It can be considered an optimization problem and can be addressed via metaheuristic algorithms. This study introduces an elite oppositional farmland fertility optimization-based node localization method for radio communication networks, called EOFFO-NLWN technique. It is the goal of the proposed EOFFO-NLWN technique to locate unknown nodes in the network by using anchor nodes as a starting point. As a result of merging the principles of elite oppositional-based learning (EOBL) and the agricultural fertility optimization algorithm (FFO), we have developed the EOFFO-NLWN approach, which is described in detail below....
Lecture notes in networks and systems, 2022
Lecture notes on data engineering and communications technologies, 2022
Intelligent Data Communication Technologies and Internet of Things, 2022
Proceedings of the 2nd International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, 2022
2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017
Abstractive multi-document summarization aims at generating new sentences whose elements originat... more Abstractive multi-document summarization aims at generating new sentences whose elements originate from different source sentence. It can be achieved via phrase selection and merging approach which aims at constructing new sentences by exploring syntactic units such as fine-grained noun and verb phrase. It can be also achieved by extracting semantic information from source sentence which uses the concept of Basic Semantic Unit (BSU) and semantic link network. Clustered semantic graph approach employs semantic role labeling and predicate argument structure to construct the summary. These approaches aim at generating efficient abstractive multi-document summarization. This paper presents the merits and demerits of the above methods in the context of abstractive text summarization.
In today’s digitalized world web is having at most information for users, additional to that news... more In today’s digitalized world web is having at most information for users, additional to that newspaper, textbook and magazine are offline resource of information. Web consist of million and billions of resources in the form of documentsin additional to that many documents in different domain are adding to it, thus data is growing exponentially. To understand and assimilate this data many applications of natural language processing came to existence namely, Text mining, Information Retrieval, Machine Translation, Question and answering, text summarization and many more. Research on text summarization started over seven decades and till now effective method or system is not available to generate summary as human. In this paper, surveys the recent literature on different automatic text summarization method and propose idea of abstractive text summarization form orphologically rich language, kannada which is still lacking in field of text summarization.
This article presents new methods for the study of language evolutions which helps researchers an... more This article presents new methods for the study of language evolutions which helps researchers and experts. Initially, a method is used to determine if the words are cognate or not. A linguistic information algorithm is proposed to derive cognates from online dictionaries. Later, a dataset is created of similar terms and machine learning techniques are used to focus on spelling in order to classify the cognates. The aligned subsequences are used to identify standards and guidelines for language change in newly created languages mainly to distinguish between non-cognates and cognates which are used for classification algorithms. Next, discriminating cognates and debts give an insight into a language's history and allow a clearer understanding of the linguistic relationship. The task of reconstruction of protowords is to recreate words from its modern daughter languages in an ancient language. The method is based on the regularity of words and use knowledge from many modern langua...
2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017
Word sense disambiguation is the process of identifying existence of polysemous words in the text... more Word sense disambiguation is the process of identifying existence of polysemous words in the text and disambiguating the appropriate sense satisfying the given context in Kannada language. The proposed methodology uses the synonyms of the target word and its surrounding words' gloss in combination with part of speech tagging to determine the overlap between the senses of the polysemous word or the target word and the words around the target word in a window to resolve the conflict among the senses of the target word.
Uploads
Papers by JAGADISH KALLIMANI